AmazonSageMakerAsync (AWS SDK for Java

All Superinterfaces:

AmazonSageMaker

All Known Implementing Classes:

AbstractAmazonSageMakerAsync, AmazonSageMakerAsyncClient
```
@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public interface AmazonSageMakerAsync
extends AmazonSageMaker
```
Interface for accessing SageMaker asynchronously. Each asynchronous method will return a Java Future object representing the asynchronous operation; overloads which accept an AsyncHandler can be used to receive notification when an asynchronous operation completes.
Note: Do not directly implement this interface, new methods are added to it regularly. Extend from AbstractAmazonSageMakerAsync instead.

Provides APIs for creating and managing SageMaker resources.

Other Resources:
- SageMaker Developer Guide
- Amazon Augmented AI Runtime API Reference

Field Summary
- Fields inherited from interface com.amazonaws.services.sagemaker.AmazonSageMaker
  ENDPOINT_PREFIX

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method and Description
`Future<AddAssociationResult>`	`addAssociationAsync(AddAssociationRequest addAssociationRequest)` Creates an association between the source and the destination.
`Future<AddAssociationResult>`	`addAssociationAsync(AddAssociationRequest addAssociationRequest, AsyncHandler<AddAssociationRequest,AddAssociationResult> asyncHandler)` Creates an association between the source and the destination.
`Future<AddTagsResult>`	`addTagsAsync(AddTagsRequest addTagsRequest)` Adds or overwrites one or more tags for the specified SageMaker resource.
`Future<AddTagsResult>`	`addTagsAsync(AddTagsRequest addTagsRequest, AsyncHandler<AddTagsRequest,AddTagsResult> asyncHandler)` Adds or overwrites one or more tags for the specified SageMaker resource.
`Future<AssociateTrialComponentResult>`	`associateTrialComponentAsync(AssociateTrialComponentRequest associateTrialComponentRequest)` Associates a trial component with a trial.
`Future<AssociateTrialComponentResult>`	`associateTrialComponentAsync(AssociateTrialComponentRequest associateTrialComponentRequest, AsyncHandler<AssociateTrialComponentRequest,AssociateTrialComponentResult> asyncHandler)` Associates a trial component with a trial.
`Future<BatchDescribeModelPackageResult>`	`batchDescribeModelPackageAsync(BatchDescribeModelPackageRequest batchDescribeModelPackageRequest)` This action batch describes a list of versioned model packages
`Future<BatchDescribeModelPackageResult>`	`batchDescribeModelPackageAsync(BatchDescribeModelPackageRequest batchDescribeModelPackageRequest, AsyncHandler<BatchDescribeModelPackageRequest,BatchDescribeModelPackageResult> asyncHandler)` This action batch describes a list of versioned model packages
`Future<CreateActionResult>`	`createActionAsync(CreateActionRequest createActionRequest)` Creates an action.
`Future<CreateActionResult>`	`createActionAsync(CreateActionRequest createActionRequest, AsyncHandler<CreateActionRequest,CreateActionResult> asyncHandler)` Creates an action.
`Future<CreateAlgorithmResult>`	`createAlgorithmAsync(CreateAlgorithmRequest createAlgorithmRequest)` Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
`Future<CreateAlgorithmResult>`	`createAlgorithmAsync(CreateAlgorithmRequest createAlgorithmRequest, AsyncHandler<CreateAlgorithmRequest,CreateAlgorithmResult> asyncHandler)` Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
`Future<CreateAppResult>`	`createAppAsync(CreateAppRequest createAppRequest)` Creates a running app for the specified UserProfile.
`Future<CreateAppResult>`	`createAppAsync(CreateAppRequest createAppRequest, AsyncHandler<CreateAppRequest,CreateAppResult> asyncHandler)` Creates a running app for the specified UserProfile.
`Future<CreateAppImageConfigResult>`	`createAppImageConfigAsync(CreateAppImageConfigRequest createAppImageConfigRequest)` Creates a configuration for running a SageMaker image as a KernelGateway app.
`Future<CreateAppImageConfigResult>`	`createAppImageConfigAsync(CreateAppImageConfigRequest createAppImageConfigRequest, AsyncHandler<CreateAppImageConfigRequest,CreateAppImageConfigResult> asyncHandler)` Creates a configuration for running a SageMaker image as a KernelGateway app.
`Future<CreateArtifactResult>`	`createArtifactAsync(CreateArtifactRequest createArtifactRequest)` Creates an artifact.
`Future<CreateArtifactResult>`	`createArtifactAsync(CreateArtifactRequest createArtifactRequest, AsyncHandler<CreateArtifactRequest,CreateArtifactResult> asyncHandler)` Creates an artifact.
`Future<CreateAutoMLJobResult>`	`createAutoMLJobAsync(CreateAutoMLJobRequest createAutoMLJobRequest)` Creates an Autopilot job.
`Future<CreateAutoMLJobResult>`	`createAutoMLJobAsync(CreateAutoMLJobRequest createAutoMLJobRequest, AsyncHandler<CreateAutoMLJobRequest,CreateAutoMLJobResult> asyncHandler)` Creates an Autopilot job.
`Future<CreateCodeRepositoryResult>`	`createCodeRepositoryAsync(CreateCodeRepositoryRequest createCodeRepositoryRequest)` Creates a Git repository as a resource in your SageMaker account.
`Future<CreateCodeRepositoryResult>`	`createCodeRepositoryAsync(CreateCodeRepositoryRequest createCodeRepositoryRequest, AsyncHandler<CreateCodeRepositoryRequest,CreateCodeRepositoryResult> asyncHandler)` Creates a Git repository as a resource in your SageMaker account.
`Future<CreateCompilationJobResult>`	`createCompilationJobAsync(CreateCompilationJobRequest createCompilationJobRequest)` Starts a model compilation job.
`Future<CreateCompilationJobResult>`	`createCompilationJobAsync(CreateCompilationJobRequest createCompilationJobRequest, AsyncHandler<CreateCompilationJobRequest,CreateCompilationJobResult> asyncHandler)` Starts a model compilation job.
`Future<CreateContextResult>`	`createContextAsync(CreateContextRequest createContextRequest)` Creates a context.
`Future<CreateContextResult>`	`createContextAsync(CreateContextRequest createContextRequest, AsyncHandler<CreateContextRequest,CreateContextResult> asyncHandler)` Creates a context.
`Future<CreateDataQualityJobDefinitionResult>`	`createDataQualityJobDefinitionAsync(CreateDataQualityJobDefinitionRequest createDataQualityJobDefinitionRequest)` Creates a definition for a job that monitors data quality and drift.
`Future<CreateDataQualityJobDefinitionResult>`	`createDataQualityJobDefinitionAsync(CreateDataQualityJobDefinitionRequest createDataQualityJobDefinitionRequest, AsyncHandler<CreateDataQualityJobDefinitionRequest,CreateDataQualityJobDefinitionResult> asyncHandler)` Creates a definition for a job that monitors data quality and drift.
`Future<CreateDeviceFleetResult>`	`createDeviceFleetAsync(CreateDeviceFleetRequest createDeviceFleetRequest)` Creates a device fleet.
`Future<CreateDeviceFleetResult>`	`createDeviceFleetAsync(CreateDeviceFleetRequest createDeviceFleetRequest, AsyncHandler<CreateDeviceFleetRequest,CreateDeviceFleetResult> asyncHandler)` Creates a device fleet.
`Future<CreateDomainResult>`	`createDomainAsync(CreateDomainRequest createDomainRequest)` Creates a `Domain` used by Amazon SageMaker Studio.
`Future<CreateDomainResult>`	`createDomainAsync(CreateDomainRequest createDomainRequest, AsyncHandler<CreateDomainRequest,CreateDomainResult> asyncHandler)` Creates a `Domain` used by Amazon SageMaker Studio.
`Future<CreateEdgePackagingJobResult>`	`createEdgePackagingJobAsync(CreateEdgePackagingJobRequest createEdgePackagingJobRequest)` Starts a SageMaker Edge Manager model packaging job.
`Future<CreateEdgePackagingJobResult>`	`createEdgePackagingJobAsync(CreateEdgePackagingJobRequest createEdgePackagingJobRequest, AsyncHandler<CreateEdgePackagingJobRequest,CreateEdgePackagingJobResult> asyncHandler)` Starts a SageMaker Edge Manager model packaging job.
`Future<CreateEndpointResult>`	`createEndpointAsync(CreateEndpointRequest createEndpointRequest)` Creates an endpoint using the endpoint configuration specified in the request.
`Future<CreateEndpointResult>`	`createEndpointAsync(CreateEndpointRequest createEndpointRequest, AsyncHandler<CreateEndpointRequest,CreateEndpointResult> asyncHandler)` Creates an endpoint using the endpoint configuration specified in the request.
`Future<CreateEndpointConfigResult>`	`createEndpointConfigAsync(CreateEndpointConfigRequest createEndpointConfigRequest)` Creates an endpoint configuration that SageMaker hosting services uses to deploy models.
`Future<CreateEndpointConfigResult>`	`createEndpointConfigAsync(CreateEndpointConfigRequest createEndpointConfigRequest, AsyncHandler<CreateEndpointConfigRequest,CreateEndpointConfigResult> asyncHandler)` Creates an endpoint configuration that SageMaker hosting services uses to deploy models.
`Future<CreateExperimentResult>`	`createExperimentAsync(CreateExperimentRequest createExperimentRequest)` Creates an SageMaker experiment.
`Future<CreateExperimentResult>`	`createExperimentAsync(CreateExperimentRequest createExperimentRequest, AsyncHandler<CreateExperimentRequest,CreateExperimentResult> asyncHandler)` Creates an SageMaker experiment.
`Future<CreateFeatureGroupResult>`	`createFeatureGroupAsync(CreateFeatureGroupRequest createFeatureGroupRequest)` Create a new `FeatureGroup`.
`Future<CreateFeatureGroupResult>`	`createFeatureGroupAsync(CreateFeatureGroupRequest createFeatureGroupRequest, AsyncHandler<CreateFeatureGroupRequest,CreateFeatureGroupResult> asyncHandler)` Create a new `FeatureGroup`.
`Future<CreateFlowDefinitionResult>`	`createFlowDefinitionAsync(CreateFlowDefinitionRequest createFlowDefinitionRequest)` Creates a flow definition.
`Future<CreateFlowDefinitionResult>`	`createFlowDefinitionAsync(CreateFlowDefinitionRequest createFlowDefinitionRequest, AsyncHandler<CreateFlowDefinitionRequest,CreateFlowDefinitionResult> asyncHandler)` Creates a flow definition.
`Future<CreateHumanTaskUiResult>`	`createHumanTaskUiAsync(CreateHumanTaskUiRequest createHumanTaskUiRequest)` Defines the settings you will use for the human review workflow user interface.
`Future<CreateHumanTaskUiResult>`	`createHumanTaskUiAsync(CreateHumanTaskUiRequest createHumanTaskUiRequest, AsyncHandler<CreateHumanTaskUiRequest,CreateHumanTaskUiResult> asyncHandler)` Defines the settings you will use for the human review workflow user interface.
`Future<CreateHyperParameterTuningJobResult>`	`createHyperParameterTuningJobAsync(CreateHyperParameterTuningJobRequest createHyperParameterTuningJobRequest)` Starts a hyperparameter tuning job.
`Future<CreateHyperParameterTuningJobResult>`	`createHyperParameterTuningJobAsync(CreateHyperParameterTuningJobRequest createHyperParameterTuningJobRequest, AsyncHandler<CreateHyperParameterTuningJobRequest,CreateHyperParameterTuningJobResult> asyncHandler)` Starts a hyperparameter tuning job.
`Future<CreateImageResult>`	`createImageAsync(CreateImageRequest createImageRequest)` Creates a custom SageMaker image.
`Future<CreateImageResult>`	`createImageAsync(CreateImageRequest createImageRequest, AsyncHandler<CreateImageRequest,CreateImageResult> asyncHandler)` Creates a custom SageMaker image.
`Future<CreateImageVersionResult>`	`createImageVersionAsync(CreateImageVersionRequest createImageVersionRequest)` Creates a version of the SageMaker image specified by `ImageName`.
`Future<CreateImageVersionResult>`	`createImageVersionAsync(CreateImageVersionRequest createImageVersionRequest, AsyncHandler<CreateImageVersionRequest,CreateImageVersionResult> asyncHandler)` Creates a version of the SageMaker image specified by `ImageName`.
`Future<CreateInferenceRecommendationsJobResult>`	`createInferenceRecommendationsJobAsync(CreateInferenceRecommendationsJobRequest createInferenceRecommendationsJobRequest)` Starts a recommendation job.
`Future<CreateInferenceRecommendationsJobResult>`	`createInferenceRecommendationsJobAsync(CreateInferenceRecommendationsJobRequest createInferenceRecommendationsJobRequest, AsyncHandler<CreateInferenceRecommendationsJobRequest,CreateInferenceRecommendationsJobResult> asyncHandler)` Starts a recommendation job.
`Future<CreateLabelingJobResult>`	`createLabelingJobAsync(CreateLabelingJobRequest createLabelingJobRequest)` Creates a job that uses workers to label the data objects in your input dataset.
`Future<CreateLabelingJobResult>`	`createLabelingJobAsync(CreateLabelingJobRequest createLabelingJobRequest, AsyncHandler<CreateLabelingJobRequest,CreateLabelingJobResult> asyncHandler)` Creates a job that uses workers to label the data objects in your input dataset.
`Future<CreateModelResult>`	`createModelAsync(CreateModelRequest createModelRequest)` Creates a model in SageMaker.
`Future<CreateModelResult>`	`createModelAsync(CreateModelRequest createModelRequest, AsyncHandler<CreateModelRequest,CreateModelResult> asyncHandler)` Creates a model in SageMaker.
`Future<CreateModelBiasJobDefinitionResult>`	`createModelBiasJobDefinitionAsync(CreateModelBiasJobDefinitionRequest createModelBiasJobDefinitionRequest)` Creates the definition for a model bias job.
`Future<CreateModelBiasJobDefinitionResult>`	`createModelBiasJobDefinitionAsync(CreateModelBiasJobDefinitionRequest createModelBiasJobDefinitionRequest, AsyncHandler<CreateModelBiasJobDefinitionRequest,CreateModelBiasJobDefinitionResult> asyncHandler)` Creates the definition for a model bias job.
`Future<CreateModelExplainabilityJobDefinitionResult>`	`createModelExplainabilityJobDefinitionAsync(CreateModelExplainabilityJobDefinitionRequest createModelExplainabilityJobDefinitionRequest)` Creates the definition for a model explainability job.
`Future<CreateModelExplainabilityJobDefinitionResult>`	`createModelExplainabilityJobDefinitionAsync(CreateModelExplainabilityJobDefinitionRequest createModelExplainabilityJobDefinitionRequest, AsyncHandler<CreateModelExplainabilityJobDefinitionRequest,CreateModelExplainabilityJobDefinitionResult> asyncHandler)` Creates the definition for a model explainability job.
`Future<CreateModelPackageResult>`	`createModelPackageAsync(CreateModelPackageRequest createModelPackageRequest)` Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group.
`Future<CreateModelPackageResult>`	`createModelPackageAsync(CreateModelPackageRequest createModelPackageRequest, AsyncHandler<CreateModelPackageRequest,CreateModelPackageResult> asyncHandler)` Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group.
`Future<CreateModelPackageGroupResult>`	`createModelPackageGroupAsync(CreateModelPackageGroupRequest createModelPackageGroupRequest)` Creates a model group.
`Future<CreateModelPackageGroupResult>`	`createModelPackageGroupAsync(CreateModelPackageGroupRequest createModelPackageGroupRequest, AsyncHandler<CreateModelPackageGroupRequest,CreateModelPackageGroupResult> asyncHandler)` Creates a model group.
`Future<CreateModelQualityJobDefinitionResult>`	`createModelQualityJobDefinitionAsync(CreateModelQualityJobDefinitionRequest createModelQualityJobDefinitionRequest)` Creates a definition for a job that monitors model quality and drift.
`Future<CreateModelQualityJobDefinitionResult>`	`createModelQualityJobDefinitionAsync(CreateModelQualityJobDefinitionRequest createModelQualityJobDefinitionRequest, AsyncHandler<CreateModelQualityJobDefinitionRequest,CreateModelQualityJobDefinitionResult> asyncHandler)` Creates a definition for a job that monitors model quality and drift.
`Future<CreateMonitoringScheduleResult>`	`createMonitoringScheduleAsync(CreateMonitoringScheduleRequest createMonitoringScheduleRequest)` Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.
`Future<CreateMonitoringScheduleResult>`	`createMonitoringScheduleAsync(CreateMonitoringScheduleRequest createMonitoringScheduleRequest, AsyncHandler<CreateMonitoringScheduleRequest,CreateMonitoringScheduleResult> asyncHandler)` Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.
`Future<CreateNotebookInstanceResult>`	`createNotebookInstanceAsync(CreateNotebookInstanceRequest createNotebookInstanceRequest)` Creates an SageMaker notebook instance.
`Future<CreateNotebookInstanceResult>`	`createNotebookInstanceAsync(CreateNotebookInstanceRequest createNotebookInstanceRequest, AsyncHandler<CreateNotebookInstanceRequest,CreateNotebookInstanceResult> asyncHandler)` Creates an SageMaker notebook instance.
`Future<CreateNotebookInstanceLifecycleConfigResult>`	`createNotebookInstanceLifecycleConfigAsync(CreateNotebookInstanceLifecycleConfigRequest createNotebookInstanceLifecycleConfigRequest)` Creates a lifecycle configuration that you can associate with a notebook instance.
`Future<CreateNotebookInstanceLifecycleConfigResult>`	`createNotebookInstanceLifecycleConfigAsync(CreateNotebookInstanceLifecycleConfigRequest createNotebookInstanceLifecycleConfigRequest, AsyncHandler<CreateNotebookInstanceLifecycleConfigRequest,CreateNotebookInstanceLifecycleConfigResult> asyncHandler)` Creates a lifecycle configuration that you can associate with a notebook instance.
`Future<CreatePipelineResult>`	`createPipelineAsync(CreatePipelineRequest createPipelineRequest)` Creates a pipeline using a JSON pipeline definition.
`Future<CreatePipelineResult>`	`createPipelineAsync(CreatePipelineRequest createPipelineRequest, AsyncHandler<CreatePipelineRequest,CreatePipelineResult> asyncHandler)` Creates a pipeline using a JSON pipeline definition.
`Future<CreatePresignedDomainUrlResult>`	`createPresignedDomainUrlAsync(CreatePresignedDomainUrlRequest createPresignedDomainUrlRequest)` Creates a URL for a specified UserProfile in a Domain.
`Future<CreatePresignedDomainUrlResult>`	`createPresignedDomainUrlAsync(CreatePresignedDomainUrlRequest createPresignedDomainUrlRequest, AsyncHandler<CreatePresignedDomainUrlRequest,CreatePresignedDomainUrlResult> asyncHandler)` Creates a URL for a specified UserProfile in a Domain.
`Future<CreatePresignedNotebookInstanceUrlResult>`	`createPresignedNotebookInstanceUrlAsync(CreatePresignedNotebookInstanceUrlRequest createPresignedNotebookInstanceUrlRequest)` Returns a URL that you can use to connect to the Jupyter server from a notebook instance.
`Future<CreatePresignedNotebookInstanceUrlResult>`	`createPresignedNotebookInstanceUrlAsync(CreatePresignedNotebookInstanceUrlRequest createPresignedNotebookInstanceUrlRequest, AsyncHandler<CreatePresignedNotebookInstanceUrlRequest,CreatePresignedNotebookInstanceUrlResult> asyncHandler)` Returns a URL that you can use to connect to the Jupyter server from a notebook instance.
`Future<CreateProcessingJobResult>`	`createProcessingJobAsync(CreateProcessingJobRequest createProcessingJobRequest)` Creates a processing job.
`Future<CreateProcessingJobResult>`	`createProcessingJobAsync(CreateProcessingJobRequest createProcessingJobRequest, AsyncHandler<CreateProcessingJobRequest,CreateProcessingJobResult> asyncHandler)` Creates a processing job.
`Future<CreateProjectResult>`	`createProjectAsync(CreateProjectRequest createProjectRequest)` Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
`Future<CreateProjectResult>`	`createProjectAsync(CreateProjectRequest createProjectRequest, AsyncHandler<CreateProjectRequest,CreateProjectResult> asyncHandler)` Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
`Future<CreateStudioLifecycleConfigResult>`	`createStudioLifecycleConfigAsync(CreateStudioLifecycleConfigRequest createStudioLifecycleConfigRequest)` Creates a new Studio Lifecycle Configuration.
`Future<CreateStudioLifecycleConfigResult>`	`createStudioLifecycleConfigAsync(CreateStudioLifecycleConfigRequest createStudioLifecycleConfigRequest, AsyncHandler<CreateStudioLifecycleConfigRequest,CreateStudioLifecycleConfigResult> asyncHandler)` Creates a new Studio Lifecycle Configuration.
`Future<CreateTrainingJobResult>`	`createTrainingJobAsync(CreateTrainingJobRequest createTrainingJobRequest)` Starts a model training job.
`Future<CreateTrainingJobResult>`	`createTrainingJobAsync(CreateTrainingJobRequest createTrainingJobRequest, AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler)` Starts a model training job.
`Future<CreateTransformJobResult>`	`createTransformJobAsync(CreateTransformJobRequest createTransformJobRequest)` Starts a transform job.
`Future<CreateTransformJobResult>`	`createTransformJobAsync(CreateTransformJobRequest createTransformJobRequest, AsyncHandler<CreateTransformJobRequest,CreateTransformJobResult> asyncHandler)` Starts a transform job.
`Future<CreateTrialResult>`	`createTrialAsync(CreateTrialRequest createTrialRequest)` Creates an SageMaker trial.
`Future<CreateTrialResult>`	`createTrialAsync(CreateTrialRequest createTrialRequest, AsyncHandler<CreateTrialRequest,CreateTrialResult> asyncHandler)` Creates an SageMaker trial.
`Future<CreateTrialComponentResult>`	`createTrialComponentAsync(CreateTrialComponentRequest createTrialComponentRequest)` Creates a trial component, which is a stage of a machine learning trial.
`Future<CreateTrialComponentResult>`	`createTrialComponentAsync(CreateTrialComponentRequest createTrialComponentRequest, AsyncHandler<CreateTrialComponentRequest,CreateTrialComponentResult> asyncHandler)` Creates a trial component, which is a stage of a machine learning trial.
`Future<CreateUserProfileResult>`	`createUserProfileAsync(CreateUserProfileRequest createUserProfileRequest)` Creates a user profile.
`Future<CreateUserProfileResult>`	`createUserProfileAsync(CreateUserProfileRequest createUserProfileRequest, AsyncHandler<CreateUserProfileRequest,CreateUserProfileResult> asyncHandler)` Creates a user profile.
`Future<CreateWorkforceResult>`	`createWorkforceAsync(CreateWorkforceRequest createWorkforceRequest)` Use this operation to create a workforce.
`Future<CreateWorkforceResult>`	`createWorkforceAsync(CreateWorkforceRequest createWorkforceRequest, AsyncHandler<CreateWorkforceRequest,CreateWorkforceResult> asyncHandler)` Use this operation to create a workforce.
`Future<CreateWorkteamResult>`	`createWorkteamAsync(CreateWorkteamRequest createWorkteamRequest)` Creates a new work team for labeling your data.
`Future<CreateWorkteamResult>`	`createWorkteamAsync(CreateWorkteamRequest createWorkteamRequest, AsyncHandler<CreateWorkteamRequest,CreateWorkteamResult> asyncHandler)` Creates a new work team for labeling your data.
`Future<DeleteActionResult>`	`deleteActionAsync(DeleteActionRequest deleteActionRequest)` Deletes an action.
`Future<DeleteActionResult>`	`deleteActionAsync(DeleteActionRequest deleteActionRequest, AsyncHandler<DeleteActionRequest,DeleteActionResult> asyncHandler)` Deletes an action.
`Future<DeleteAlgorithmResult>`	`deleteAlgorithmAsync(DeleteAlgorithmRequest deleteAlgorithmRequest)` Removes the specified algorithm from your account.
`Future<DeleteAlgorithmResult>`	`deleteAlgorithmAsync(DeleteAlgorithmRequest deleteAlgorithmRequest, AsyncHandler<DeleteAlgorithmRequest,DeleteAlgorithmResult> asyncHandler)` Removes the specified algorithm from your account.
`Future<DeleteAppResult>`	`deleteAppAsync(DeleteAppRequest deleteAppRequest)` Used to stop and delete an app.
`Future<DeleteAppResult>`	`deleteAppAsync(DeleteAppRequest deleteAppRequest, AsyncHandler<DeleteAppRequest,DeleteAppResult> asyncHandler)` Used to stop and delete an app.
`Future<DeleteAppImageConfigResult>`	`deleteAppImageConfigAsync(DeleteAppImageConfigRequest deleteAppImageConfigRequest)` Deletes an AppImageConfig.
`Future<DeleteAppImageConfigResult>`	`deleteAppImageConfigAsync(DeleteAppImageConfigRequest deleteAppImageConfigRequest, AsyncHandler<DeleteAppImageConfigRequest,DeleteAppImageConfigResult> asyncHandler)` Deletes an AppImageConfig.
`Future<DeleteArtifactResult>`	`deleteArtifactAsync(DeleteArtifactRequest deleteArtifactRequest)` Deletes an artifact.
`Future<DeleteArtifactResult>`	`deleteArtifactAsync(DeleteArtifactRequest deleteArtifactRequest, AsyncHandler<DeleteArtifactRequest,DeleteArtifactResult> asyncHandler)` Deletes an artifact.
`Future<DeleteAssociationResult>`	`deleteAssociationAsync(DeleteAssociationRequest deleteAssociationRequest)` Deletes an association.
`Future<DeleteAssociationResult>`	`deleteAssociationAsync(DeleteAssociationRequest deleteAssociationRequest, AsyncHandler<DeleteAssociationRequest,DeleteAssociationResult> asyncHandler)` Deletes an association.
`Future<DeleteCodeRepositoryResult>`	`deleteCodeRepositoryAsync(DeleteCodeRepositoryRequest deleteCodeRepositoryRequest)` Deletes the specified Git repository from your account.
`Future<DeleteCodeRepositoryResult>`	`deleteCodeRepositoryAsync(DeleteCodeRepositoryRequest deleteCodeRepositoryRequest, AsyncHandler<DeleteCodeRepositoryRequest,DeleteCodeRepositoryResult> asyncHandler)` Deletes the specified Git repository from your account.
`Future<DeleteContextResult>`	`deleteContextAsync(DeleteContextRequest deleteContextRequest)` Deletes an context.
`Future<DeleteContextResult>`	`deleteContextAsync(DeleteContextRequest deleteContextRequest, AsyncHandler<DeleteContextRequest,DeleteContextResult> asyncHandler)` Deletes an context.
`Future<DeleteDataQualityJobDefinitionResult>`	`deleteDataQualityJobDefinitionAsync(DeleteDataQualityJobDefinitionRequest deleteDataQualityJobDefinitionRequest)` Deletes a data quality monitoring job definition.
`Future<DeleteDataQualityJobDefinitionResult>`	`deleteDataQualityJobDefinitionAsync(DeleteDataQualityJobDefinitionRequest deleteDataQualityJobDefinitionRequest, AsyncHandler<DeleteDataQualityJobDefinitionRequest,DeleteDataQualityJobDefinitionResult> asyncHandler)` Deletes a data quality monitoring job definition.
`Future<DeleteDeviceFleetResult>`	`deleteDeviceFleetAsync(DeleteDeviceFleetRequest deleteDeviceFleetRequest)` Deletes a fleet.
`Future<DeleteDeviceFleetResult>`	`deleteDeviceFleetAsync(DeleteDeviceFleetRequest deleteDeviceFleetRequest, AsyncHandler<DeleteDeviceFleetRequest,DeleteDeviceFleetResult> asyncHandler)` Deletes a fleet.
`Future<DeleteDomainResult>`	`deleteDomainAsync(DeleteDomainRequest deleteDomainRequest)` Used to delete a domain.
`Future<DeleteDomainResult>`	`deleteDomainAsync(DeleteDomainRequest deleteDomainRequest, AsyncHandler<DeleteDomainRequest,DeleteDomainResult> asyncHandler)` Used to delete a domain.
`Future<DeleteEndpointResult>`	`deleteEndpointAsync(DeleteEndpointRequest deleteEndpointRequest)` Deletes an endpoint.
`Future<DeleteEndpointResult>`	`deleteEndpointAsync(DeleteEndpointRequest deleteEndpointRequest, AsyncHandler<DeleteEndpointRequest,DeleteEndpointResult> asyncHandler)` Deletes an endpoint.
`Future<DeleteEndpointConfigResult>`	`deleteEndpointConfigAsync(DeleteEndpointConfigRequest deleteEndpointConfigRequest)` Deletes an endpoint configuration.
`Future<DeleteEndpointConfigResult>`	`deleteEndpointConfigAsync(DeleteEndpointConfigRequest deleteEndpointConfigRequest, AsyncHandler<DeleteEndpointConfigRequest,DeleteEndpointConfigResult> asyncHandler)` Deletes an endpoint configuration.
`Future<DeleteExperimentResult>`	`deleteExperimentAsync(DeleteExperimentRequest deleteExperimentRequest)` Deletes an SageMaker experiment.
`Future<DeleteExperimentResult>`	`deleteExperimentAsync(DeleteExperimentRequest deleteExperimentRequest, AsyncHandler<DeleteExperimentRequest,DeleteExperimentResult> asyncHandler)` Deletes an SageMaker experiment.
`Future<DeleteFeatureGroupResult>`	`deleteFeatureGroupAsync(DeleteFeatureGroupRequest deleteFeatureGroupRequest)` Delete the `FeatureGroup` and any data that was written to the `OnlineStore` of the `FeatureGroup`.
`Future<DeleteFeatureGroupResult>`	`deleteFeatureGroupAsync(DeleteFeatureGroupRequest deleteFeatureGroupRequest, AsyncHandler<DeleteFeatureGroupRequest,DeleteFeatureGroupResult> asyncHandler)` Delete the `FeatureGroup` and any data that was written to the `OnlineStore` of the `FeatureGroup`.
`Future<DeleteFlowDefinitionResult>`	`deleteFlowDefinitionAsync(DeleteFlowDefinitionRequest deleteFlowDefinitionRequest)` Deletes the specified flow definition.
`Future<DeleteFlowDefinitionResult>`	`deleteFlowDefinitionAsync(DeleteFlowDefinitionRequest deleteFlowDefinitionRequest, AsyncHandler<DeleteFlowDefinitionRequest,DeleteFlowDefinitionResult> asyncHandler)` Deletes the specified flow definition.
`Future<DeleteHumanTaskUiResult>`	`deleteHumanTaskUiAsync(DeleteHumanTaskUiRequest deleteHumanTaskUiRequest)` Use this operation to delete a human task user interface (worker task template).
`Future<DeleteHumanTaskUiResult>`	`deleteHumanTaskUiAsync(DeleteHumanTaskUiRequest deleteHumanTaskUiRequest, AsyncHandler<DeleteHumanTaskUiRequest,DeleteHumanTaskUiResult> asyncHandler)` Use this operation to delete a human task user interface (worker task template).
`Future<DeleteImageResult>`	`deleteImageAsync(DeleteImageRequest deleteImageRequest)` Deletes a SageMaker image and all versions of the image.
`Future<DeleteImageResult>`	`deleteImageAsync(DeleteImageRequest deleteImageRequest, AsyncHandler<DeleteImageRequest,DeleteImageResult> asyncHandler)` Deletes a SageMaker image and all versions of the image.
`Future<DeleteImageVersionResult>`	`deleteImageVersionAsync(DeleteImageVersionRequest deleteImageVersionRequest)` Deletes a version of a SageMaker image.
`Future<DeleteImageVersionResult>`	`deleteImageVersionAsync(DeleteImageVersionRequest deleteImageVersionRequest, AsyncHandler<DeleteImageVersionRequest,DeleteImageVersionResult> asyncHandler)` Deletes a version of a SageMaker image.
`Future<DeleteModelResult>`	`deleteModelAsync(DeleteModelRequest deleteModelRequest)` Deletes a model.
`Future<DeleteModelResult>`	`deleteModelAsync(DeleteModelRequest deleteModelRequest, AsyncHandler<DeleteModelRequest,DeleteModelResult> asyncHandler)` Deletes a model.
`Future<DeleteModelBiasJobDefinitionResult>`	`deleteModelBiasJobDefinitionAsync(DeleteModelBiasJobDefinitionRequest deleteModelBiasJobDefinitionRequest)` Deletes an Amazon SageMaker model bias job definition.
`Future<DeleteModelBiasJobDefinitionResult>`	`deleteModelBiasJobDefinitionAsync(DeleteModelBiasJobDefinitionRequest deleteModelBiasJobDefinitionRequest, AsyncHandler<DeleteModelBiasJobDefinitionRequest,DeleteModelBiasJobDefinitionResult> asyncHandler)` Deletes an Amazon SageMaker model bias job definition.
`Future<DeleteModelExplainabilityJobDefinitionResult>`	`deleteModelExplainabilityJobDefinitionAsync(DeleteModelExplainabilityJobDefinitionRequest deleteModelExplainabilityJobDefinitionRequest)` Deletes an Amazon SageMaker model explainability job definition.
`Future<DeleteModelExplainabilityJobDefinitionResult>`	`deleteModelExplainabilityJobDefinitionAsync(DeleteModelExplainabilityJobDefinitionRequest deleteModelExplainabilityJobDefinitionRequest, AsyncHandler<DeleteModelExplainabilityJobDefinitionRequest,DeleteModelExplainabilityJobDefinitionResult> asyncHandler)` Deletes an Amazon SageMaker model explainability job definition.
`Future<DeleteModelPackageResult>`	`deleteModelPackageAsync(DeleteModelPackageRequest deleteModelPackageRequest)` Deletes a model package.
`Future<DeleteModelPackageResult>`	`deleteModelPackageAsync(DeleteModelPackageRequest deleteModelPackageRequest, AsyncHandler<DeleteModelPackageRequest,DeleteModelPackageResult> asyncHandler)` Deletes a model package.
`Future<DeleteModelPackageGroupResult>`	`deleteModelPackageGroupAsync(DeleteModelPackageGroupRequest deleteModelPackageGroupRequest)` Deletes the specified model group.
`Future<DeleteModelPackageGroupResult>`	`deleteModelPackageGroupAsync(DeleteModelPackageGroupRequest deleteModelPackageGroupRequest, AsyncHandler<DeleteModelPackageGroupRequest,DeleteModelPackageGroupResult> asyncHandler)` Deletes the specified model group.
`Future<DeleteModelPackageGroupPolicyResult>`	`deleteModelPackageGroupPolicyAsync(DeleteModelPackageGroupPolicyRequest deleteModelPackageGroupPolicyRequest)` Deletes a model group resource policy.
`Future<DeleteModelPackageGroupPolicyResult>`	`deleteModelPackageGroupPolicyAsync(DeleteModelPackageGroupPolicyRequest deleteModelPackageGroupPolicyRequest, AsyncHandler<DeleteModelPackageGroupPolicyRequest,DeleteModelPackageGroupPolicyResult> asyncHandler)` Deletes a model group resource policy.
`Future<DeleteModelQualityJobDefinitionResult>`	`deleteModelQualityJobDefinitionAsync(DeleteModelQualityJobDefinitionRequest deleteModelQualityJobDefinitionRequest)` Deletes the secified model quality monitoring job definition.
`Future<DeleteModelQualityJobDefinitionResult>`	`deleteModelQualityJobDefinitionAsync(DeleteModelQualityJobDefinitionRequest deleteModelQualityJobDefinitionRequest, AsyncHandler<DeleteModelQualityJobDefinitionRequest,DeleteModelQualityJobDefinitionResult> asyncHandler)` Deletes the secified model quality monitoring job definition.
`Future<DeleteMonitoringScheduleResult>`	`deleteMonitoringScheduleAsync(DeleteMonitoringScheduleRequest deleteMonitoringScheduleRequest)` Deletes a monitoring schedule.
`Future<DeleteMonitoringScheduleResult>`	`deleteMonitoringScheduleAsync(DeleteMonitoringScheduleRequest deleteMonitoringScheduleRequest, AsyncHandler<DeleteMonitoringScheduleRequest,DeleteMonitoringScheduleResult> asyncHandler)` Deletes a monitoring schedule.
`Future<DeleteNotebookInstanceResult>`	`deleteNotebookInstanceAsync(DeleteNotebookInstanceRequest deleteNotebookInstanceRequest)` Deletes an SageMaker notebook instance.
`Future<DeleteNotebookInstanceResult>`	`deleteNotebookInstanceAsync(DeleteNotebookInstanceRequest deleteNotebookInstanceRequest, AsyncHandler<DeleteNotebookInstanceRequest,DeleteNotebookInstanceResult> asyncHandler)` Deletes an SageMaker notebook instance.
`Future<DeleteNotebookInstanceLifecycleConfigResult>`	`deleteNotebookInstanceLifecycleConfigAsync(DeleteNotebookInstanceLifecycleConfigRequest deleteNotebookInstanceLifecycleConfigRequest)` Deletes a notebook instance lifecycle configuration.
`Future<DeleteNotebookInstanceLifecycleConfigResult>`	`deleteNotebookInstanceLifecycleConfigAsync(DeleteNotebookInstanceLifecycleConfigRequest deleteNotebookInstanceLifecycleConfigRequest, AsyncHandler<DeleteNotebookInstanceLifecycleConfigRequest,DeleteNotebookInstanceLifecycleConfigResult> asyncHandler)` Deletes a notebook instance lifecycle configuration.
`Future<DeletePipelineResult>`	`deletePipelineAsync(DeletePipelineRequest deletePipelineRequest)` Deletes a pipeline if there are no running instances of the pipeline.
`Future<DeletePipelineResult>`	`deletePipelineAsync(DeletePipelineRequest deletePipelineRequest, AsyncHandler<DeletePipelineRequest,DeletePipelineResult> asyncHandler)` Deletes a pipeline if there are no running instances of the pipeline.
`Future<DeleteProjectResult>`	`deleteProjectAsync(DeleteProjectRequest deleteProjectRequest)` Delete the specified project.
`Future<DeleteProjectResult>`	`deleteProjectAsync(DeleteProjectRequest deleteProjectRequest, AsyncHandler<DeleteProjectRequest,DeleteProjectResult> asyncHandler)` Delete the specified project.
`Future<DeleteStudioLifecycleConfigResult>`	`deleteStudioLifecycleConfigAsync(DeleteStudioLifecycleConfigRequest deleteStudioLifecycleConfigRequest)` Deletes the Studio Lifecycle Configuration.
`Future<DeleteStudioLifecycleConfigResult>`	`deleteStudioLifecycleConfigAsync(DeleteStudioLifecycleConfigRequest deleteStudioLifecycleConfigRequest, AsyncHandler<DeleteStudioLifecycleConfigRequest,DeleteStudioLifecycleConfigResult> asyncHandler)` Deletes the Studio Lifecycle Configuration.
`Future<DeleteTagsResult>`	`deleteTagsAsync(DeleteTagsRequest deleteTagsRequest)` Deletes the specified tags from an SageMaker resource.
`Future<DeleteTagsResult>`	`deleteTagsAsync(DeleteTagsRequest deleteTagsRequest, AsyncHandler<DeleteTagsRequest,DeleteTagsResult> asyncHandler)` Deletes the specified tags from an SageMaker resource.
`Future<DeleteTrialResult>`	`deleteTrialAsync(DeleteTrialRequest deleteTrialRequest)` Deletes the specified trial.
`Future<DeleteTrialResult>`	`deleteTrialAsync(DeleteTrialRequest deleteTrialRequest, AsyncHandler<DeleteTrialRequest,DeleteTrialResult> asyncHandler)` Deletes the specified trial.
`Future<DeleteTrialComponentResult>`	`deleteTrialComponentAsync(DeleteTrialComponentRequest deleteTrialComponentRequest)` Deletes the specified trial component.
`Future<DeleteTrialComponentResult>`	`deleteTrialComponentAsync(DeleteTrialComponentRequest deleteTrialComponentRequest, AsyncHandler<DeleteTrialComponentRequest,DeleteTrialComponentResult> asyncHandler)` Deletes the specified trial component.
`Future<DeleteUserProfileResult>`	`deleteUserProfileAsync(DeleteUserProfileRequest deleteUserProfileRequest)` Deletes a user profile.
`Future<DeleteUserProfileResult>`	`deleteUserProfileAsync(DeleteUserProfileRequest deleteUserProfileRequest, AsyncHandler<DeleteUserProfileRequest,DeleteUserProfileResult> asyncHandler)` Deletes a user profile.
`Future<DeleteWorkforceResult>`	`deleteWorkforceAsync(DeleteWorkforceRequest deleteWorkforceRequest)` Use this operation to delete a workforce.
`Future<DeleteWorkforceResult>`	`deleteWorkforceAsync(DeleteWorkforceRequest deleteWorkforceRequest, AsyncHandler<DeleteWorkforceRequest,DeleteWorkforceResult> asyncHandler)` Use this operation to delete a workforce.
`Future<DeleteWorkteamResult>`	`deleteWorkteamAsync(DeleteWorkteamRequest deleteWorkteamRequest)` Deletes an existing work team.
`Future<DeleteWorkteamResult>`	`deleteWorkteamAsync(DeleteWorkteamRequest deleteWorkteamRequest, AsyncHandler<DeleteWorkteamRequest,DeleteWorkteamResult> asyncHandler)` Deletes an existing work team.
`Future<DeregisterDevicesResult>`	`deregisterDevicesAsync(DeregisterDevicesRequest deregisterDevicesRequest)` Deregisters the specified devices.
`Future<DeregisterDevicesResult>`	`deregisterDevicesAsync(DeregisterDevicesRequest deregisterDevicesRequest, AsyncHandler<DeregisterDevicesRequest,DeregisterDevicesResult> asyncHandler)` Deregisters the specified devices.
`Future<DescribeActionResult>`	`describeActionAsync(DescribeActionRequest describeActionRequest)` Describes an action.
`Future<DescribeActionResult>`	`describeActionAsync(DescribeActionRequest describeActionRequest, AsyncHandler<DescribeActionRequest,DescribeActionResult> asyncHandler)` Describes an action.
`Future<DescribeAlgorithmResult>`	`describeAlgorithmAsync(DescribeAlgorithmRequest describeAlgorithmRequest)` Returns a description of the specified algorithm that is in your account.
`Future<DescribeAlgorithmResult>`	`describeAlgorithmAsync(DescribeAlgorithmRequest describeAlgorithmRequest, AsyncHandler<DescribeAlgorithmRequest,DescribeAlgorithmResult> asyncHandler)` Returns a description of the specified algorithm that is in your account.
`Future<DescribeAppResult>`	`describeAppAsync(DescribeAppRequest describeAppRequest)` Describes the app.
`Future<DescribeAppResult>`	`describeAppAsync(DescribeAppRequest describeAppRequest, AsyncHandler<DescribeAppRequest,DescribeAppResult> asyncHandler)` Describes the app.
`Future<DescribeAppImageConfigResult>`	`describeAppImageConfigAsync(DescribeAppImageConfigRequest describeAppImageConfigRequest)` Describes an AppImageConfig.
`Future<DescribeAppImageConfigResult>`	`describeAppImageConfigAsync(DescribeAppImageConfigRequest describeAppImageConfigRequest, AsyncHandler<DescribeAppImageConfigRequest,DescribeAppImageConfigResult> asyncHandler)` Describes an AppImageConfig.
`Future<DescribeArtifactResult>`	`describeArtifactAsync(DescribeArtifactRequest describeArtifactRequest)` Describes an artifact.
`Future<DescribeArtifactResult>`	`describeArtifactAsync(DescribeArtifactRequest describeArtifactRequest, AsyncHandler<DescribeArtifactRequest,DescribeArtifactResult> asyncHandler)` Describes an artifact.
`Future<DescribeAutoMLJobResult>`	`describeAutoMLJobAsync(DescribeAutoMLJobRequest describeAutoMLJobRequest)` Returns information about an Amazon SageMaker AutoML job.
`Future<DescribeAutoMLJobResult>`	`describeAutoMLJobAsync(DescribeAutoMLJobRequest describeAutoMLJobRequest, AsyncHandler<DescribeAutoMLJobRequest,DescribeAutoMLJobResult> asyncHandler)` Returns information about an Amazon SageMaker AutoML job.
`Future<DescribeCodeRepositoryResult>`	`describeCodeRepositoryAsync(DescribeCodeRepositoryRequest describeCodeRepositoryRequest)` Gets details about the specified Git repository.
`Future<DescribeCodeRepositoryResult>`	`describeCodeRepositoryAsync(DescribeCodeRepositoryRequest describeCodeRepositoryRequest, AsyncHandler<DescribeCodeRepositoryRequest,DescribeCodeRepositoryResult> asyncHandler)` Gets details about the specified Git repository.
`Future<DescribeCompilationJobResult>`	`describeCompilationJobAsync(DescribeCompilationJobRequest describeCompilationJobRequest)` Returns information about a model compilation job.
`Future<DescribeCompilationJobResult>`	`describeCompilationJobAsync(DescribeCompilationJobRequest describeCompilationJobRequest, AsyncHandler<DescribeCompilationJobRequest,DescribeCompilationJobResult> asyncHandler)` Returns information about a model compilation job.
`Future<DescribeContextResult>`	`describeContextAsync(DescribeContextRequest describeContextRequest)` Describes a context.
`Future<DescribeContextResult>`	`describeContextAsync(DescribeContextRequest describeContextRequest, AsyncHandler<DescribeContextRequest,DescribeContextResult> asyncHandler)` Describes a context.
`Future<DescribeDataQualityJobDefinitionResult>`	`describeDataQualityJobDefinitionAsync(DescribeDataQualityJobDefinitionRequest describeDataQualityJobDefinitionRequest)` Gets the details of a data quality monitoring job definition.
`Future<DescribeDataQualityJobDefinitionResult>`	`describeDataQualityJobDefinitionAsync(DescribeDataQualityJobDefinitionRequest describeDataQualityJobDefinitionRequest, AsyncHandler<DescribeDataQualityJobDefinitionRequest,DescribeDataQualityJobDefinitionResult> asyncHandler)` Gets the details of a data quality monitoring job definition.
`Future<DescribeDeviceResult>`	`describeDeviceAsync(DescribeDeviceRequest describeDeviceRequest)` Describes the device.
`Future<DescribeDeviceResult>`	`describeDeviceAsync(DescribeDeviceRequest describeDeviceRequest, AsyncHandler<DescribeDeviceRequest,DescribeDeviceResult> asyncHandler)` Describes the device.
`Future<DescribeDeviceFleetResult>`	`describeDeviceFleetAsync(DescribeDeviceFleetRequest describeDeviceFleetRequest)` A description of the fleet the device belongs to.
`Future<DescribeDeviceFleetResult>`	`describeDeviceFleetAsync(DescribeDeviceFleetRequest describeDeviceFleetRequest, AsyncHandler<DescribeDeviceFleetRequest,DescribeDeviceFleetResult> asyncHandler)` A description of the fleet the device belongs to.
`Future<DescribeDomainResult>`	`describeDomainAsync(DescribeDomainRequest describeDomainRequest)` The description of the domain.
`Future<DescribeDomainResult>`	`describeDomainAsync(DescribeDomainRequest describeDomainRequest, AsyncHandler<DescribeDomainRequest,DescribeDomainResult> asyncHandler)` The description of the domain.
`Future<DescribeEdgePackagingJobResult>`	`describeEdgePackagingJobAsync(DescribeEdgePackagingJobRequest describeEdgePackagingJobRequest)` A description of edge packaging jobs.
`Future<DescribeEdgePackagingJobResult>`	`describeEdgePackagingJobAsync(DescribeEdgePackagingJobRequest describeEdgePackagingJobRequest, AsyncHandler<DescribeEdgePackagingJobRequest,DescribeEdgePackagingJobResult> asyncHandler)` A description of edge packaging jobs.
`Future<DescribeEndpointResult>`	`describeEndpointAsync(DescribeEndpointRequest describeEndpointRequest)` Returns the description of an endpoint.
`Future<DescribeEndpointResult>`	`describeEndpointAsync(DescribeEndpointRequest describeEndpointRequest, AsyncHandler<DescribeEndpointRequest,DescribeEndpointResult> asyncHandler)` Returns the description of an endpoint.
`Future<DescribeEndpointConfigResult>`	`describeEndpointConfigAsync(DescribeEndpointConfigRequest describeEndpointConfigRequest)` Returns the description of an endpoint configuration created using the `CreateEndpointConfig` API.
`Future<DescribeEndpointConfigResult>`	`describeEndpointConfigAsync(DescribeEndpointConfigRequest describeEndpointConfigRequest, AsyncHandler<DescribeEndpointConfigRequest,DescribeEndpointConfigResult> asyncHandler)` Returns the description of an endpoint configuration created using the `CreateEndpointConfig` API.
`Future<DescribeExperimentResult>`	`describeExperimentAsync(DescribeExperimentRequest describeExperimentRequest)` Provides a list of an experiment's properties.
`Future<DescribeExperimentResult>`	`describeExperimentAsync(DescribeExperimentRequest describeExperimentRequest, AsyncHandler<DescribeExperimentRequest,DescribeExperimentResult> asyncHandler)` Provides a list of an experiment's properties.
`Future<DescribeFeatureGroupResult>`	`describeFeatureGroupAsync(DescribeFeatureGroupRequest describeFeatureGroupRequest)` Use this operation to describe a `FeatureGroup`.
`Future<DescribeFeatureGroupResult>`	`describeFeatureGroupAsync(DescribeFeatureGroupRequest describeFeatureGroupRequest, AsyncHandler<DescribeFeatureGroupRequest,DescribeFeatureGroupResult> asyncHandler)` Use this operation to describe a `FeatureGroup`.
`Future<DescribeFlowDefinitionResult>`	`describeFlowDefinitionAsync(DescribeFlowDefinitionRequest describeFlowDefinitionRequest)` Returns information about the specified flow definition.
`Future<DescribeFlowDefinitionResult>`	`describeFlowDefinitionAsync(DescribeFlowDefinitionRequest describeFlowDefinitionRequest, AsyncHandler<DescribeFlowDefinitionRequest,DescribeFlowDefinitionResult> asyncHandler)` Returns information about the specified flow definition.
`Future<DescribeHumanTaskUiResult>`	`describeHumanTaskUiAsync(DescribeHumanTaskUiRequest describeHumanTaskUiRequest)` Returns information about the requested human task user interface (worker task template).
`Future<DescribeHumanTaskUiResult>`	`describeHumanTaskUiAsync(DescribeHumanTaskUiRequest describeHumanTaskUiRequest, AsyncHandler<DescribeHumanTaskUiRequest,DescribeHumanTaskUiResult> asyncHandler)` Returns information about the requested human task user interface (worker task template).
`Future<DescribeHyperParameterTuningJobResult>`	`describeHyperParameterTuningJobAsync(DescribeHyperParameterTuningJobRequest describeHyperParameterTuningJobRequest)` Gets a description of a hyperparameter tuning job.
`Future<DescribeHyperParameterTuningJobResult>`	`describeHyperParameterTuningJobAsync(DescribeHyperParameterTuningJobRequest describeHyperParameterTuningJobRequest, AsyncHandler<DescribeHyperParameterTuningJobRequest,DescribeHyperParameterTuningJobResult> asyncHandler)` Gets a description of a hyperparameter tuning job.
`Future<DescribeImageResult>`	`describeImageAsync(DescribeImageRequest describeImageRequest)` Describes a SageMaker image.
`Future<DescribeImageResult>`	`describeImageAsync(DescribeImageRequest describeImageRequest, AsyncHandler<DescribeImageRequest,DescribeImageResult> asyncHandler)` Describes a SageMaker image.
`Future<DescribeImageVersionResult>`	`describeImageVersionAsync(DescribeImageVersionRequest describeImageVersionRequest)` Describes a version of a SageMaker image.
`Future<DescribeImageVersionResult>`	`describeImageVersionAsync(DescribeImageVersionRequest describeImageVersionRequest, AsyncHandler<DescribeImageVersionRequest,DescribeImageVersionResult> asyncHandler)` Describes a version of a SageMaker image.
`Future<DescribeInferenceRecommendationsJobResult>`	`describeInferenceRecommendationsJobAsync(DescribeInferenceRecommendationsJobRequest describeInferenceRecommendationsJobRequest)` Provides the results of the Inference Recommender job.
`Future<DescribeInferenceRecommendationsJobResult>`	`describeInferenceRecommendationsJobAsync(DescribeInferenceRecommendationsJobRequest describeInferenceRecommendationsJobRequest, AsyncHandler<DescribeInferenceRecommendationsJobRequest,DescribeInferenceRecommendationsJobResult> asyncHandler)` Provides the results of the Inference Recommender job.
`Future<DescribeLabelingJobResult>`	`describeLabelingJobAsync(DescribeLabelingJobRequest describeLabelingJobRequest)` Gets information about a labeling job.
`Future<DescribeLabelingJobResult>`	`describeLabelingJobAsync(DescribeLabelingJobRequest describeLabelingJobRequest, AsyncHandler<DescribeLabelingJobRequest,DescribeLabelingJobResult> asyncHandler)` Gets information about a labeling job.
`Future<DescribeLineageGroupResult>`	`describeLineageGroupAsync(DescribeLineageGroupRequest describeLineageGroupRequest)` Provides a list of properties for the requested lineage group.
`Future<DescribeLineageGroupResult>`	`describeLineageGroupAsync(DescribeLineageGroupRequest describeLineageGroupRequest, AsyncHandler<DescribeLineageGroupRequest,DescribeLineageGroupResult> asyncHandler)` Provides a list of properties for the requested lineage group.
`Future<DescribeModelResult>`	`describeModelAsync(DescribeModelRequest describeModelRequest)` Describes a model that you created using the `CreateModel` API.
`Future<DescribeModelResult>`	`describeModelAsync(DescribeModelRequest describeModelRequest, AsyncHandler<DescribeModelRequest,DescribeModelResult> asyncHandler)` Describes a model that you created using the `CreateModel` API.
`Future<DescribeModelBiasJobDefinitionResult>`	`describeModelBiasJobDefinitionAsync(DescribeModelBiasJobDefinitionRequest describeModelBiasJobDefinitionRequest)` Returns a description of a model bias job definition.
`Future<DescribeModelBiasJobDefinitionResult>`	`describeModelBiasJobDefinitionAsync(DescribeModelBiasJobDefinitionRequest describeModelBiasJobDefinitionRequest, AsyncHandler<DescribeModelBiasJobDefinitionRequest,DescribeModelBiasJobDefinitionResult> asyncHandler)` Returns a description of a model bias job definition.
`Future<DescribeModelExplainabilityJobDefinitionResult>`	`describeModelExplainabilityJobDefinitionAsync(DescribeModelExplainabilityJobDefinitionRequest describeModelExplainabilityJobDefinitionRequest)` Returns a description of a model explainability job definition.
`Future<DescribeModelExplainabilityJobDefinitionResult>`	`describeModelExplainabilityJobDefinitionAsync(DescribeModelExplainabilityJobDefinitionRequest describeModelExplainabilityJobDefinitionRequest, AsyncHandler<DescribeModelExplainabilityJobDefinitionRequest,DescribeModelExplainabilityJobDefinitionResult> asyncHandler)` Returns a description of a model explainability job definition.
`Future<DescribeModelPackageResult>`	`describeModelPackageAsync(DescribeModelPackageRequest describeModelPackageRequest)` Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
`Future<DescribeModelPackageResult>`	`describeModelPackageAsync(DescribeModelPackageRequest describeModelPackageRequest, AsyncHandler<DescribeModelPackageRequest,DescribeModelPackageResult> asyncHandler)` Returns a description of the specified model package, which is used to create SageMaker models or list them on Amazon Web Services Marketplace.
`Future<DescribeModelPackageGroupResult>`	`describeModelPackageGroupAsync(DescribeModelPackageGroupRequest describeModelPackageGroupRequest)` Gets a description for the specified model group.
`Future<DescribeModelPackageGroupResult>`	`describeModelPackageGroupAsync(DescribeModelPackageGroupRequest describeModelPackageGroupRequest, AsyncHandler<DescribeModelPackageGroupRequest,DescribeModelPackageGroupResult> asyncHandler)` Gets a description for the specified model group.
`Future<DescribeModelQualityJobDefinitionResult>`	`describeModelQualityJobDefinitionAsync(DescribeModelQualityJobDefinitionRequest describeModelQualityJobDefinitionRequest)` Returns a description of a model quality job definition.
`Future<DescribeModelQualityJobDefinitionResult>`	`describeModelQualityJobDefinitionAsync(DescribeModelQualityJobDefinitionRequest describeModelQualityJobDefinitionRequest, AsyncHandler<DescribeModelQualityJobDefinitionRequest,DescribeModelQualityJobDefinitionResult> asyncHandler)` Returns a description of a model quality job definition.
`Future<DescribeMonitoringScheduleResult>`	`describeMonitoringScheduleAsync(DescribeMonitoringScheduleRequest describeMonitoringScheduleRequest)` Describes the schedule for a monitoring job.
`Future<DescribeMonitoringScheduleResult>`	`describeMonitoringScheduleAsync(DescribeMonitoringScheduleRequest describeMonitoringScheduleRequest, AsyncHandler<DescribeMonitoringScheduleRequest,DescribeMonitoringScheduleResult> asyncHandler)` Describes the schedule for a monitoring job.
`Future<DescribeNotebookInstanceResult>`	`describeNotebookInstanceAsync(DescribeNotebookInstanceRequest describeNotebookInstanceRequest)` Returns information about a notebook instance.
`Future<DescribeNotebookInstanceResult>`	`describeNotebookInstanceAsync(DescribeNotebookInstanceRequest describeNotebookInstanceRequest, AsyncHandler<DescribeNotebookInstanceRequest,DescribeNotebookInstanceResult> asyncHandler)` Returns information about a notebook instance.
`Future<DescribeNotebookInstanceLifecycleConfigResult>`	`describeNotebookInstanceLifecycleConfigAsync(DescribeNotebookInstanceLifecycleConfigRequest describeNotebookInstanceLifecycleConfigRequest)` Returns a description of a notebook instance lifecycle configuration.
`Future<DescribeNotebookInstanceLifecycleConfigResult>`	`describeNotebookInstanceLifecycleConfigAsync(DescribeNotebookInstanceLifecycleConfigRequest describeNotebookInstanceLifecycleConfigRequest, AsyncHandler<DescribeNotebookInstanceLifecycleConfigRequest,DescribeNotebookInstanceLifecycleConfigResult> asyncHandler)` Returns a description of a notebook instance lifecycle configuration.
`Future<DescribePipelineResult>`	`describePipelineAsync(DescribePipelineRequest describePipelineRequest)` Describes the details of a pipeline.
`Future<DescribePipelineResult>`	`describePipelineAsync(DescribePipelineRequest describePipelineRequest, AsyncHandler<DescribePipelineRequest,DescribePipelineResult> asyncHandler)` Describes the details of a pipeline.
`Future<DescribePipelineDefinitionForExecutionResult>`	`describePipelineDefinitionForExecutionAsync(DescribePipelineDefinitionForExecutionRequest describePipelineDefinitionForExecutionRequest)` Describes the details of an execution's pipeline definition.
`Future<DescribePipelineDefinitionForExecutionResult>`	`describePipelineDefinitionForExecutionAsync(DescribePipelineDefinitionForExecutionRequest describePipelineDefinitionForExecutionRequest, AsyncHandler<DescribePipelineDefinitionForExecutionRequest,DescribePipelineDefinitionForExecutionResult> asyncHandler)` Describes the details of an execution's pipeline definition.
`Future<DescribePipelineExecutionResult>`	`describePipelineExecutionAsync(DescribePipelineExecutionRequest describePipelineExecutionRequest)` Describes the details of a pipeline execution.
`Future<DescribePipelineExecutionResult>`	`describePipelineExecutionAsync(DescribePipelineExecutionRequest describePipelineExecutionRequest, AsyncHandler<DescribePipelineExecutionRequest,DescribePipelineExecutionResult> asyncHandler)` Describes the details of a pipeline execution.
`Future<DescribeProcessingJobResult>`	`describeProcessingJobAsync(DescribeProcessingJobRequest describeProcessingJobRequest)` Returns a description of a processing job.
`Future<DescribeProcessingJobResult>`	`describeProcessingJobAsync(DescribeProcessingJobRequest describeProcessingJobRequest, AsyncHandler<DescribeProcessingJobRequest,DescribeProcessingJobResult> asyncHandler)` Returns a description of a processing job.
`Future<DescribeProjectResult>`	`describeProjectAsync(DescribeProjectRequest describeProjectRequest)` Describes the details of a project.
`Future<DescribeProjectResult>`	`describeProjectAsync(DescribeProjectRequest describeProjectRequest, AsyncHandler<DescribeProjectRequest,DescribeProjectResult> asyncHandler)` Describes the details of a project.
`Future<DescribeStudioLifecycleConfigResult>`	`describeStudioLifecycleConfigAsync(DescribeStudioLifecycleConfigRequest describeStudioLifecycleConfigRequest)` Describes the Studio Lifecycle Configuration.
`Future<DescribeStudioLifecycleConfigResult>`	`describeStudioLifecycleConfigAsync(DescribeStudioLifecycleConfigRequest describeStudioLifecycleConfigRequest, AsyncHandler<DescribeStudioLifecycleConfigRequest,DescribeStudioLifecycleConfigResult> asyncHandler)` Describes the Studio Lifecycle Configuration.
`Future<DescribeSubscribedWorkteamResult>`	`describeSubscribedWorkteamAsync(DescribeSubscribedWorkteamRequest describeSubscribedWorkteamRequest)` Gets information about a work team provided by a vendor.
`Future<DescribeSubscribedWorkteamResult>`	`describeSubscribedWorkteamAsync(DescribeSubscribedWorkteamRequest describeSubscribedWorkteamRequest, AsyncHandler<DescribeSubscribedWorkteamRequest,DescribeSubscribedWorkteamResult> asyncHandler)` Gets information about a work team provided by a vendor.
`Future<DescribeTrainingJobResult>`	`describeTrainingJobAsync(DescribeTrainingJobRequest describeTrainingJobRequest)` Returns information about a training job.
`Future<DescribeTrainingJobResult>`	`describeTrainingJobAsync(DescribeTrainingJobRequest describeTrainingJobRequest, AsyncHandler<DescribeTrainingJobRequest,DescribeTrainingJobResult> asyncHandler)` Returns information about a training job.
`Future<DescribeTransformJobResult>`	`describeTransformJobAsync(DescribeTransformJobRequest describeTransformJobRequest)` Returns information about a transform job.
`Future<DescribeTransformJobResult>`	`describeTransformJobAsync(DescribeTransformJobRequest describeTransformJobRequest, AsyncHandler<DescribeTransformJobRequest,DescribeTransformJobResult> asyncHandler)` Returns information about a transform job.
`Future<DescribeTrialResult>`	`describeTrialAsync(DescribeTrialRequest describeTrialRequest)` Provides a list of a trial's properties.
`Future<DescribeTrialResult>`	`describeTrialAsync(DescribeTrialRequest describeTrialRequest, AsyncHandler<DescribeTrialRequest,DescribeTrialResult> asyncHandler)` Provides a list of a trial's properties.
`Future<DescribeTrialComponentResult>`	`describeTrialComponentAsync(DescribeTrialComponentRequest describeTrialComponentRequest)` Provides a list of a trials component's properties.
`Future<DescribeTrialComponentResult>`	`describeTrialComponentAsync(DescribeTrialComponentRequest describeTrialComponentRequest, AsyncHandler<DescribeTrialComponentRequest,DescribeTrialComponentResult> asyncHandler)` Provides a list of a trials component's properties.
`Future<DescribeUserProfileResult>`	`describeUserProfileAsync(DescribeUserProfileRequest describeUserProfileRequest)` Describes a user profile.
`Future<DescribeUserProfileResult>`	`describeUserProfileAsync(DescribeUserProfileRequest describeUserProfileRequest, AsyncHandler<DescribeUserProfileRequest,DescribeUserProfileResult> asyncHandler)` Describes a user profile.
`Future<DescribeWorkforceResult>`	`describeWorkforceAsync(DescribeWorkforceRequest describeWorkforceRequest)` Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs).
`Future<DescribeWorkforceResult>`	`describeWorkforceAsync(DescribeWorkforceRequest describeWorkforceRequest, AsyncHandler<DescribeWorkforceRequest,DescribeWorkforceResult> asyncHandler)` Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs).
`Future<DescribeWorkteamResult>`	`describeWorkteamAsync(DescribeWorkteamRequest describeWorkteamRequest)` Gets information about a specific work team.
`Future<DescribeWorkteamResult>`	`describeWorkteamAsync(DescribeWorkteamRequest describeWorkteamRequest, AsyncHandler<DescribeWorkteamRequest,DescribeWorkteamResult> asyncHandler)` Gets information about a specific work team.
`Future<DisableSagemakerServicecatalogPortfolioResult>`	`disableSagemakerServicecatalogPortfolioAsync(DisableSagemakerServicecatalogPortfolioRequest disableSagemakerServicecatalogPortfolioRequest)` Disables using Service Catalog in SageMaker.
`Future<DisableSagemakerServicecatalogPortfolioResult>`	`disableSagemakerServicecatalogPortfolioAsync(DisableSagemakerServicecatalogPortfolioRequest disableSagemakerServicecatalogPortfolioRequest, AsyncHandler<DisableSagemakerServicecatalogPortfolioRequest,DisableSagemakerServicecatalogPortfolioResult> asyncHandler)` Disables using Service Catalog in SageMaker.
`Future<DisassociateTrialComponentResult>`	`disassociateTrialComponentAsync(DisassociateTrialComponentRequest disassociateTrialComponentRequest)` Disassociates a trial component from a trial.
`Future<DisassociateTrialComponentResult>`	`disassociateTrialComponentAsync(DisassociateTrialComponentRequest disassociateTrialComponentRequest, AsyncHandler<DisassociateTrialComponentRequest,DisassociateTrialComponentResult> asyncHandler)` Disassociates a trial component from a trial.
`Future<EnableSagemakerServicecatalogPortfolioResult>`	`enableSagemakerServicecatalogPortfolioAsync(EnableSagemakerServicecatalogPortfolioRequest enableSagemakerServicecatalogPortfolioRequest)` Enables using Service Catalog in SageMaker.
`Future<EnableSagemakerServicecatalogPortfolioResult>`	`enableSagemakerServicecatalogPortfolioAsync(EnableSagemakerServicecatalogPortfolioRequest enableSagemakerServicecatalogPortfolioRequest, AsyncHandler<EnableSagemakerServicecatalogPortfolioRequest,EnableSagemakerServicecatalogPortfolioResult> asyncHandler)` Enables using Service Catalog in SageMaker.
`Future<GetDeviceFleetReportResult>`	`getDeviceFleetReportAsync(GetDeviceFleetReportRequest getDeviceFleetReportRequest)` Describes a fleet.
`Future<GetDeviceFleetReportResult>`	`getDeviceFleetReportAsync(GetDeviceFleetReportRequest getDeviceFleetReportRequest, AsyncHandler<GetDeviceFleetReportRequest,GetDeviceFleetReportResult> asyncHandler)` Describes a fleet.
`Future<GetLineageGroupPolicyResult>`	`getLineageGroupPolicyAsync(GetLineageGroupPolicyRequest getLineageGroupPolicyRequest)` The resource policy for the lineage group.
`Future<GetLineageGroupPolicyResult>`	`getLineageGroupPolicyAsync(GetLineageGroupPolicyRequest getLineageGroupPolicyRequest, AsyncHandler<GetLineageGroupPolicyRequest,GetLineageGroupPolicyResult> asyncHandler)` The resource policy for the lineage group.
`Future<GetModelPackageGroupPolicyResult>`	`getModelPackageGroupPolicyAsync(GetModelPackageGroupPolicyRequest getModelPackageGroupPolicyRequest)` Gets a resource policy that manages access for a model group.
`Future<GetModelPackageGroupPolicyResult>`	`getModelPackageGroupPolicyAsync(GetModelPackageGroupPolicyRequest getModelPackageGroupPolicyRequest, AsyncHandler<GetModelPackageGroupPolicyRequest,GetModelPackageGroupPolicyResult> asyncHandler)` Gets a resource policy that manages access for a model group.
`Future<GetSagemakerServicecatalogPortfolioStatusResult>`	`getSagemakerServicecatalogPortfolioStatusAsync(GetSagemakerServicecatalogPortfolioStatusRequest getSagemakerServicecatalogPortfolioStatusRequest)` Gets the status of Service Catalog in SageMaker.
`Future<GetSagemakerServicecatalogPortfolioStatusResult>`	`getSagemakerServicecatalogPortfolioStatusAsync(GetSagemakerServicecatalogPortfolioStatusRequest getSagemakerServicecatalogPortfolioStatusRequest, AsyncHandler<GetSagemakerServicecatalogPortfolioStatusRequest,GetSagemakerServicecatalogPortfolioStatusResult> asyncHandler)` Gets the status of Service Catalog in SageMaker.
`Future<GetSearchSuggestionsResult>`	`getSearchSuggestionsAsync(GetSearchSuggestionsRequest getSearchSuggestionsRequest)` An auto-complete API for the search functionality in the Amazon SageMaker console.
`Future<GetSearchSuggestionsResult>`	`getSearchSuggestionsAsync(GetSearchSuggestionsRequest getSearchSuggestionsRequest, AsyncHandler<GetSearchSuggestionsRequest,GetSearchSuggestionsResult> asyncHandler)` An auto-complete API for the search functionality in the Amazon SageMaker console.
`Future<ListActionsResult>`	`listActionsAsync(ListActionsRequest listActionsRequest)` Lists the actions in your account and their properties.
`Future<ListActionsResult>`	`listActionsAsync(ListActionsRequest listActionsRequest, AsyncHandler<ListActionsRequest,ListActionsResult> asyncHandler)` Lists the actions in your account and their properties.
`Future<ListAlgorithmsResult>`	`listAlgorithmsAsync(ListAlgorithmsRequest listAlgorithmsRequest)` Lists the machine learning algorithms that have been created.
`Future<ListAlgorithmsResult>`	`listAlgorithmsAsync(ListAlgorithmsRequest listAlgorithmsRequest, AsyncHandler<ListAlgorithmsRequest,ListAlgorithmsResult> asyncHandler)` Lists the machine learning algorithms that have been created.
`Future<ListAppImageConfigsResult>`	`listAppImageConfigsAsync(ListAppImageConfigsRequest listAppImageConfigsRequest)` Lists the AppImageConfigs in your account and their properties.
`Future<ListAppImageConfigsResult>`	`listAppImageConfigsAsync(ListAppImageConfigsRequest listAppImageConfigsRequest, AsyncHandler<ListAppImageConfigsRequest,ListAppImageConfigsResult> asyncHandler)` Lists the AppImageConfigs in your account and their properties.
`Future<ListAppsResult>`	`listAppsAsync(ListAppsRequest listAppsRequest)` Lists apps.
`Future<ListAppsResult>`	`listAppsAsync(ListAppsRequest listAppsRequest, AsyncHandler<ListAppsRequest,ListAppsResult> asyncHandler)` Lists apps.
`Future<ListArtifactsResult>`	`listArtifactsAsync(ListArtifactsRequest listArtifactsRequest)` Lists the artifacts in your account and their properties.
`Future<ListArtifactsResult>`	`listArtifactsAsync(ListArtifactsRequest listArtifactsRequest, AsyncHandler<ListArtifactsRequest,ListArtifactsResult> asyncHandler)` Lists the artifacts in your account and their properties.
`Future<ListAssociationsResult>`	`listAssociationsAsync(ListAssociationsRequest listAssociationsRequest)` Lists the associations in your account and their properties.
`Future<ListAssociationsResult>`	`listAssociationsAsync(ListAssociationsRequest listAssociationsRequest, AsyncHandler<ListAssociationsRequest,ListAssociationsResult> asyncHandler)` Lists the associations in your account and their properties.
`Future<ListAutoMLJobsResult>`	`listAutoMLJobsAsync(ListAutoMLJobsRequest listAutoMLJobsRequest)` Request a list of jobs.
`Future<ListAutoMLJobsResult>`	`listAutoMLJobsAsync(ListAutoMLJobsRequest listAutoMLJobsRequest, AsyncHandler<ListAutoMLJobsRequest,ListAutoMLJobsResult> asyncHandler)` Request a list of jobs.
`Future<ListCandidatesForAutoMLJobResult>`	`listCandidatesForAutoMLJobAsync(ListCandidatesForAutoMLJobRequest listCandidatesForAutoMLJobRequest)` List the candidates created for the job.
`Future<ListCandidatesForAutoMLJobResult>`	`listCandidatesForAutoMLJobAsync(ListCandidatesForAutoMLJobRequest listCandidatesForAutoMLJobRequest, AsyncHandler<ListCandidatesForAutoMLJobRequest,ListCandidatesForAutoMLJobResult> asyncHandler)` List the candidates created for the job.
`Future<ListCodeRepositoriesResult>`	`listCodeRepositoriesAsync(ListCodeRepositoriesRequest listCodeRepositoriesRequest)` Gets a list of the Git repositories in your account.
`Future<ListCodeRepositoriesResult>`	`listCodeRepositoriesAsync(ListCodeRepositoriesRequest listCodeRepositoriesRequest, AsyncHandler<ListCodeRepositoriesRequest,ListCodeRepositoriesResult> asyncHandler)` Gets a list of the Git repositories in your account.
`Future<ListCompilationJobsResult>`	`listCompilationJobsAsync(ListCompilationJobsRequest listCompilationJobsRequest)` Lists model compilation jobs that satisfy various filters.
`Future<ListCompilationJobsResult>`	`listCompilationJobsAsync(ListCompilationJobsRequest listCompilationJobsRequest, AsyncHandler<ListCompilationJobsRequest,ListCompilationJobsResult> asyncHandler)` Lists model compilation jobs that satisfy various filters.
`Future<ListContextsResult>`	`listContextsAsync(ListContextsRequest listContextsRequest)` Lists the contexts in your account and their properties.
`Future<ListContextsResult>`	`listContextsAsync(ListContextsRequest listContextsRequest, AsyncHandler<ListContextsRequest,ListContextsResult> asyncHandler)` Lists the contexts in your account and their properties.
`Future<ListDataQualityJobDefinitionsResult>`	`listDataQualityJobDefinitionsAsync(ListDataQualityJobDefinitionsRequest listDataQualityJobDefinitionsRequest)` Lists the data quality job definitions in your account.
`Future<ListDataQualityJobDefinitionsResult>`	`listDataQualityJobDefinitionsAsync(ListDataQualityJobDefinitionsRequest listDataQualityJobDefinitionsRequest, AsyncHandler<ListDataQualityJobDefinitionsRequest,ListDataQualityJobDefinitionsResult> asyncHandler)` Lists the data quality job definitions in your account.
`Future<ListDeviceFleetsResult>`	`listDeviceFleetsAsync(ListDeviceFleetsRequest listDeviceFleetsRequest)` Returns a list of devices in the fleet.
`Future<ListDeviceFleetsResult>`	`listDeviceFleetsAsync(ListDeviceFleetsRequest listDeviceFleetsRequest, AsyncHandler<ListDeviceFleetsRequest,ListDeviceFleetsResult> asyncHandler)` Returns a list of devices in the fleet.
`Future<ListDevicesResult>`	`listDevicesAsync(ListDevicesRequest listDevicesRequest)` A list of devices.
`Future<ListDevicesResult>`	`listDevicesAsync(ListDevicesRequest listDevicesRequest, AsyncHandler<ListDevicesRequest,ListDevicesResult> asyncHandler)` A list of devices.
`Future<ListDomainsResult>`	`listDomainsAsync(ListDomainsRequest listDomainsRequest)` Lists the domains.
`Future<ListDomainsResult>`	`listDomainsAsync(ListDomainsRequest listDomainsRequest, AsyncHandler<ListDomainsRequest,ListDomainsResult> asyncHandler)` Lists the domains.
`Future<ListEdgePackagingJobsResult>`	`listEdgePackagingJobsAsync(ListEdgePackagingJobsRequest listEdgePackagingJobsRequest)` Returns a list of edge packaging jobs.
`Future<ListEdgePackagingJobsResult>`	`listEdgePackagingJobsAsync(ListEdgePackagingJobsRequest listEdgePackagingJobsRequest, AsyncHandler<ListEdgePackagingJobsRequest,ListEdgePackagingJobsResult> asyncHandler)` Returns a list of edge packaging jobs.
`Future<ListEndpointConfigsResult>`	`listEndpointConfigsAsync(ListEndpointConfigsRequest listEndpointConfigsRequest)` Lists endpoint configurations.
`Future<ListEndpointConfigsResult>`	`listEndpointConfigsAsync(ListEndpointConfigsRequest listEndpointConfigsRequest, AsyncHandler<ListEndpointConfigsRequest,ListEndpointConfigsResult> asyncHandler)` Lists endpoint configurations.
`Future<ListEndpointsResult>`	`listEndpointsAsync(ListEndpointsRequest listEndpointsRequest)` Lists endpoints.
`Future<ListEndpointsResult>`	`listEndpointsAsync(ListEndpointsRequest listEndpointsRequest, AsyncHandler<ListEndpointsRequest,ListEndpointsResult> asyncHandler)` Lists endpoints.
`Future<ListExperimentsResult>`	`listExperimentsAsync(ListExperimentsRequest listExperimentsRequest)` Lists all the experiments in your account.
`Future<ListExperimentsResult>`	`listExperimentsAsync(ListExperimentsRequest listExperimentsRequest, AsyncHandler<ListExperimentsRequest,ListExperimentsResult> asyncHandler)` Lists all the experiments in your account.
`Future<ListFeatureGroupsResult>`	`listFeatureGroupsAsync(ListFeatureGroupsRequest listFeatureGroupsRequest)` List `FeatureGroup`s based on given filter and order.
`Future<ListFeatureGroupsResult>`	`listFeatureGroupsAsync(ListFeatureGroupsRequest listFeatureGroupsRequest, AsyncHandler<ListFeatureGroupsRequest,ListFeatureGroupsResult> asyncHandler)` List `FeatureGroup`s based on given filter and order.
`Future<ListFlowDefinitionsResult>`	`listFlowDefinitionsAsync(ListFlowDefinitionsRequest listFlowDefinitionsRequest)` Returns information about the flow definitions in your account.
`Future<ListFlowDefinitionsResult>`	`listFlowDefinitionsAsync(ListFlowDefinitionsRequest listFlowDefinitionsRequest, AsyncHandler<ListFlowDefinitionsRequest,ListFlowDefinitionsResult> asyncHandler)` Returns information about the flow definitions in your account.
`Future<ListHumanTaskUisResult>`	`listHumanTaskUisAsync(ListHumanTaskUisRequest listHumanTaskUisRequest)` Returns information about the human task user interfaces in your account.
`Future<ListHumanTaskUisResult>`	`listHumanTaskUisAsync(ListHumanTaskUisRequest listHumanTaskUisRequest, AsyncHandler<ListHumanTaskUisRequest,ListHumanTaskUisResult> asyncHandler)` Returns information about the human task user interfaces in your account.
`Future<ListHyperParameterTuningJobsResult>`	`listHyperParameterTuningJobsAsync(ListHyperParameterTuningJobsRequest listHyperParameterTuningJobsRequest)` Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
`Future<ListHyperParameterTuningJobsResult>`	`listHyperParameterTuningJobsAsync(ListHyperParameterTuningJobsRequest listHyperParameterTuningJobsRequest, AsyncHandler<ListHyperParameterTuningJobsRequest,ListHyperParameterTuningJobsResult> asyncHandler)` Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.
`Future<ListImagesResult>`	`listImagesAsync(ListImagesRequest listImagesRequest)` Lists the images in your account and their properties.
`Future<ListImagesResult>`	`listImagesAsync(ListImagesRequest listImagesRequest, AsyncHandler<ListImagesRequest,ListImagesResult> asyncHandler)` Lists the images in your account and their properties.
`Future<ListImageVersionsResult>`	`listImageVersionsAsync(ListImageVersionsRequest listImageVersionsRequest)` Lists the versions of a specified image and their properties.
`Future<ListImageVersionsResult>`	`listImageVersionsAsync(ListImageVersionsRequest listImageVersionsRequest, AsyncHandler<ListImageVersionsRequest,ListImageVersionsResult> asyncHandler)` Lists the versions of a specified image and their properties.
`Future<ListInferenceRecommendationsJobsResult>`	`listInferenceRecommendationsJobsAsync(ListInferenceRecommendationsJobsRequest listInferenceRecommendationsJobsRequest)` Lists recommendation jobs that satisfy various filters.
`Future<ListInferenceRecommendationsJobsResult>`	`listInferenceRecommendationsJobsAsync(ListInferenceRecommendationsJobsRequest listInferenceRecommendationsJobsRequest, AsyncHandler<ListInferenceRecommendationsJobsRequest,ListInferenceRecommendationsJobsResult> asyncHandler)` Lists recommendation jobs that satisfy various filters.
`Future<ListLabelingJobsResult>`	`listLabelingJobsAsync(ListLabelingJobsRequest listLabelingJobsRequest)` Gets a list of labeling jobs.
`Future<ListLabelingJobsResult>`	`listLabelingJobsAsync(ListLabelingJobsRequest listLabelingJobsRequest, AsyncHandler<ListLabelingJobsRequest,ListLabelingJobsResult> asyncHandler)` Gets a list of labeling jobs.
`Future<ListLabelingJobsForWorkteamResult>`	`listLabelingJobsForWorkteamAsync(ListLabelingJobsForWorkteamRequest listLabelingJobsForWorkteamRequest)` Gets a list of labeling jobs assigned to a specified work team.
`Future<ListLabelingJobsForWorkteamResult>`	`listLabelingJobsForWorkteamAsync(ListLabelingJobsForWorkteamRequest listLabelingJobsForWorkteamRequest, AsyncHandler<ListLabelingJobsForWorkteamRequest,ListLabelingJobsForWorkteamResult> asyncHandler)` Gets a list of labeling jobs assigned to a specified work team.
`Future<ListLineageGroupsResult>`	`listLineageGroupsAsync(ListLineageGroupsRequest listLineageGroupsRequest)` A list of lineage groups shared with your Amazon Web Services account.
`Future<ListLineageGroupsResult>`	`listLineageGroupsAsync(ListLineageGroupsRequest listLineageGroupsRequest, AsyncHandler<ListLineageGroupsRequest,ListLineageGroupsResult> asyncHandler)` A list of lineage groups shared with your Amazon Web Services account.
`Future<ListModelBiasJobDefinitionsResult>`	`listModelBiasJobDefinitionsAsync(ListModelBiasJobDefinitionsRequest listModelBiasJobDefinitionsRequest)` Lists model bias jobs definitions that satisfy various filters.
`Future<ListModelBiasJobDefinitionsResult>`	`listModelBiasJobDefinitionsAsync(ListModelBiasJobDefinitionsRequest listModelBiasJobDefinitionsRequest, AsyncHandler<ListModelBiasJobDefinitionsRequest,ListModelBiasJobDefinitionsResult> asyncHandler)` Lists model bias jobs definitions that satisfy various filters.
`Future<ListModelExplainabilityJobDefinitionsResult>`	`listModelExplainabilityJobDefinitionsAsync(ListModelExplainabilityJobDefinitionsRequest listModelExplainabilityJobDefinitionsRequest)` Lists model explainability job definitions that satisfy various filters.
`Future<ListModelExplainabilityJobDefinitionsResult>`	`listModelExplainabilityJobDefinitionsAsync(ListModelExplainabilityJobDefinitionsRequest listModelExplainabilityJobDefinitionsRequest, AsyncHandler<ListModelExplainabilityJobDefinitionsRequest,ListModelExplainabilityJobDefinitionsResult> asyncHandler)` Lists model explainability job definitions that satisfy various filters.
`Future<ListModelMetadataResult>`	`listModelMetadataAsync(ListModelMetadataRequest listModelMetadataRequest)` Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
`Future<ListModelMetadataResult>`	`listModelMetadataAsync(ListModelMetadataRequest listModelMetadataRequest, AsyncHandler<ListModelMetadataRequest,ListModelMetadataResult> asyncHandler)` Lists the domain, framework, task, and model name of standard machine learning models found in common model zoos.
`Future<ListModelPackageGroupsResult>`	`listModelPackageGroupsAsync(ListModelPackageGroupsRequest listModelPackageGroupsRequest)` Gets a list of the model groups in your Amazon Web Services account.
`Future<ListModelPackageGroupsResult>`	`listModelPackageGroupsAsync(ListModelPackageGroupsRequest listModelPackageGroupsRequest, AsyncHandler<ListModelPackageGroupsRequest,ListModelPackageGroupsResult> asyncHandler)` Gets a list of the model groups in your Amazon Web Services account.
`Future<ListModelPackagesResult>`	`listModelPackagesAsync(ListModelPackagesRequest listModelPackagesRequest)` Lists the model packages that have been created.
`Future<ListModelPackagesResult>`	`listModelPackagesAsync(ListModelPackagesRequest listModelPackagesRequest, AsyncHandler<ListModelPackagesRequest,ListModelPackagesResult> asyncHandler)` Lists the model packages that have been created.
`Future<ListModelQualityJobDefinitionsResult>`	`listModelQualityJobDefinitionsAsync(ListModelQualityJobDefinitionsRequest listModelQualityJobDefinitionsRequest)` Gets a list of model quality monitoring job definitions in your account.
`Future<ListModelQualityJobDefinitionsResult>`	`listModelQualityJobDefinitionsAsync(ListModelQualityJobDefinitionsRequest listModelQualityJobDefinitionsRequest, AsyncHandler<ListModelQualityJobDefinitionsRequest,ListModelQualityJobDefinitionsResult> asyncHandler)` Gets a list of model quality monitoring job definitions in your account.
`Future<ListModelsResult>`	`listModelsAsync(ListModelsRequest listModelsRequest)` Lists models created with the `CreateModel` API.
`Future<ListModelsResult>`	`listModelsAsync(ListModelsRequest listModelsRequest, AsyncHandler<ListModelsRequest,ListModelsResult> asyncHandler)` Lists models created with the `CreateModel` API.
`Future<ListMonitoringExecutionsResult>`	`listMonitoringExecutionsAsync(ListMonitoringExecutionsRequest listMonitoringExecutionsRequest)` Returns list of all monitoring job executions.
`Future<ListMonitoringExecutionsResult>`	`listMonitoringExecutionsAsync(ListMonitoringExecutionsRequest listMonitoringExecutionsRequest, AsyncHandler<ListMonitoringExecutionsRequest,ListMonitoringExecutionsResult> asyncHandler)` Returns list of all monitoring job executions.
`Future<ListMonitoringSchedulesResult>`	`listMonitoringSchedulesAsync(ListMonitoringSchedulesRequest listMonitoringSchedulesRequest)` Returns list of all monitoring schedules.
`Future<ListMonitoringSchedulesResult>`	`listMonitoringSchedulesAsync(ListMonitoringSchedulesRequest listMonitoringSchedulesRequest, AsyncHandler<ListMonitoringSchedulesRequest,ListMonitoringSchedulesResult> asyncHandler)` Returns list of all monitoring schedules.
`Future<ListNotebookInstanceLifecycleConfigsResult>`	`listNotebookInstanceLifecycleConfigsAsync(ListNotebookInstanceLifecycleConfigsRequest listNotebookInstanceLifecycleConfigsRequest)` Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
`Future<ListNotebookInstanceLifecycleConfigsResult>`	`listNotebookInstanceLifecycleConfigsAsync(ListNotebookInstanceLifecycleConfigsRequest listNotebookInstanceLifecycleConfigsRequest, AsyncHandler<ListNotebookInstanceLifecycleConfigsRequest,ListNotebookInstanceLifecycleConfigsResult> asyncHandler)` Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.
`Future<ListNotebookInstancesResult>`	`listNotebookInstancesAsync(ListNotebookInstancesRequest listNotebookInstancesRequest)` Returns a list of the SageMaker notebook instances in the requester's account in an Amazon Web Services Region.
`Future<ListNotebookInstancesResult>`	`listNotebookInstancesAsync(ListNotebookInstancesRequest listNotebookInstancesRequest, AsyncHandler<ListNotebookInstancesRequest,ListNotebookInstancesResult> asyncHandler)` Returns a list of the SageMaker notebook instances in the requester's account in an Amazon Web Services Region.
`Future<ListPipelineExecutionsResult>`	`listPipelineExecutionsAsync(ListPipelineExecutionsRequest listPipelineExecutionsRequest)` Gets a list of the pipeline executions.
`Future<ListPipelineExecutionsResult>`	`listPipelineExecutionsAsync(ListPipelineExecutionsRequest listPipelineExecutionsRequest, AsyncHandler<ListPipelineExecutionsRequest,ListPipelineExecutionsResult> asyncHandler)` Gets a list of the pipeline executions.
`Future<ListPipelineExecutionStepsResult>`	`listPipelineExecutionStepsAsync(ListPipelineExecutionStepsRequest listPipelineExecutionStepsRequest)` Gets a list of `PipeLineExecutionStep` objects.
`Future<ListPipelineExecutionStepsResult>`	`listPipelineExecutionStepsAsync(ListPipelineExecutionStepsRequest listPipelineExecutionStepsRequest, AsyncHandler<ListPipelineExecutionStepsRequest,ListPipelineExecutionStepsResult> asyncHandler)` Gets a list of `PipeLineExecutionStep` objects.
`Future<ListPipelineParametersForExecutionResult>`	`listPipelineParametersForExecutionAsync(ListPipelineParametersForExecutionRequest listPipelineParametersForExecutionRequest)` Gets a list of parameters for a pipeline execution.
`Future<ListPipelineParametersForExecutionResult>`	`listPipelineParametersForExecutionAsync(ListPipelineParametersForExecutionRequest listPipelineParametersForExecutionRequest, AsyncHandler<ListPipelineParametersForExecutionRequest,ListPipelineParametersForExecutionResult> asyncHandler)` Gets a list of parameters for a pipeline execution.
`Future<ListPipelinesResult>`	`listPipelinesAsync(ListPipelinesRequest listPipelinesRequest)` Gets a list of pipelines.
`Future<ListPipelinesResult>`	`listPipelinesAsync(ListPipelinesRequest listPipelinesRequest, AsyncHandler<ListPipelinesRequest,ListPipelinesResult> asyncHandler)` Gets a list of pipelines.
`Future<ListProcessingJobsResult>`	`listProcessingJobsAsync(ListProcessingJobsRequest listProcessingJobsRequest)` Lists processing jobs that satisfy various filters.
`Future<ListProcessingJobsResult>`	`listProcessingJobsAsync(ListProcessingJobsRequest listProcessingJobsRequest, AsyncHandler<ListProcessingJobsRequest,ListProcessingJobsResult> asyncHandler)` Lists processing jobs that satisfy various filters.
`Future<ListProjectsResult>`	`listProjectsAsync(ListProjectsRequest listProjectsRequest)` Gets a list of the projects in an Amazon Web Services account.
`Future<ListProjectsResult>`	`listProjectsAsync(ListProjectsRequest listProjectsRequest, AsyncHandler<ListProjectsRequest,ListProjectsResult> asyncHandler)` Gets a list of the projects in an Amazon Web Services account.
`Future<ListStudioLifecycleConfigsResult>`	`listStudioLifecycleConfigsAsync(ListStudioLifecycleConfigsRequest listStudioLifecycleConfigsRequest)` Lists the Studio Lifecycle Configurations in your Amazon Web Services Account.
`Future<ListStudioLifecycleConfigsResult>`	`listStudioLifecycleConfigsAsync(ListStudioLifecycleConfigsRequest listStudioLifecycleConfigsRequest, AsyncHandler<ListStudioLifecycleConfigsRequest,ListStudioLifecycleConfigsResult> asyncHandler)` Lists the Studio Lifecycle Configurations in your Amazon Web Services Account.
`Future<ListSubscribedWorkteamsResult>`	`listSubscribedWorkteamsAsync(ListSubscribedWorkteamsRequest listSubscribedWorkteamsRequest)` Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace.
`Future<ListSubscribedWorkteamsResult>`	`listSubscribedWorkteamsAsync(ListSubscribedWorkteamsRequest listSubscribedWorkteamsRequest, AsyncHandler<ListSubscribedWorkteamsRequest,ListSubscribedWorkteamsResult> asyncHandler)` Gets a list of the work teams that you are subscribed to in the Amazon Web Services Marketplace.
`Future<ListTagsResult>`	`listTagsAsync(ListTagsRequest listTagsRequest)` Returns the tags for the specified SageMaker resource.
`Future<ListTagsResult>`	`listTagsAsync(ListTagsRequest listTagsRequest, AsyncHandler<ListTagsRequest,ListTagsResult> asyncHandler)` Returns the tags for the specified SageMaker resource.
`Future<ListTrainingJobsResult>`	`listTrainingJobsAsync(ListTrainingJobsRequest listTrainingJobsRequest)` Lists training jobs.
`Future<ListTrainingJobsResult>`	`listTrainingJobsAsync(ListTrainingJobsRequest listTrainingJobsRequest, AsyncHandler<ListTrainingJobsRequest,ListTrainingJobsResult> asyncHandler)` Lists training jobs.
`Future<ListTrainingJobsForHyperParameterTuningJobResult>`	`listTrainingJobsForHyperParameterTuningJobAsync(ListTrainingJobsForHyperParameterTuningJobRequest listTrainingJobsForHyperParameterTuningJobRequest)` Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
`Future<ListTrainingJobsForHyperParameterTuningJobResult>`	`listTrainingJobsForHyperParameterTuningJobAsync(ListTrainingJobsForHyperParameterTuningJobRequest listTrainingJobsForHyperParameterTuningJobRequest, AsyncHandler<ListTrainingJobsForHyperParameterTuningJobRequest,ListTrainingJobsForHyperParameterTuningJobResult> asyncHandler)` Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.
`Future<ListTransformJobsResult>`	`listTransformJobsAsync(ListTransformJobsRequest listTransformJobsRequest)` Lists transform jobs.
`Future<ListTransformJobsResult>`	`listTransformJobsAsync(ListTransformJobsRequest listTransformJobsRequest, AsyncHandler<ListTransformJobsRequest,ListTransformJobsResult> asyncHandler)` Lists transform jobs.
`Future<ListTrialComponentsResult>`	`listTrialComponentsAsync(ListTrialComponentsRequest listTrialComponentsRequest)` Lists the trial components in your account.
`Future<ListTrialComponentsResult>`	`listTrialComponentsAsync(ListTrialComponentsRequest listTrialComponentsRequest, AsyncHandler<ListTrialComponentsRequest,ListTrialComponentsResult> asyncHandler)` Lists the trial components in your account.
`Future<ListTrialsResult>`	`listTrialsAsync(ListTrialsRequest listTrialsRequest)` Lists the trials in your account.
`Future<ListTrialsResult>`	`listTrialsAsync(ListTrialsRequest listTrialsRequest, AsyncHandler<ListTrialsRequest,ListTrialsResult> asyncHandler)` Lists the trials in your account.
`Future<ListUserProfilesResult>`	`listUserProfilesAsync(ListUserProfilesRequest listUserProfilesRequest)` Lists user profiles.
`Future<ListUserProfilesResult>`	`listUserProfilesAsync(ListUserProfilesRequest listUserProfilesRequest, AsyncHandler<ListUserProfilesRequest,ListUserProfilesResult> asyncHandler)` Lists user profiles.
`Future<ListWorkforcesResult>`	`listWorkforcesAsync(ListWorkforcesRequest listWorkforcesRequest)` Use this operation to list all private and vendor workforces in an Amazon Web Services Region.
`Future<ListWorkforcesResult>`	`listWorkforcesAsync(ListWorkforcesRequest listWorkforcesRequest, AsyncHandler<ListWorkforcesRequest,ListWorkforcesResult> asyncHandler)` Use this operation to list all private and vendor workforces in an Amazon Web Services Region.
`Future<ListWorkteamsResult>`	`listWorkteamsAsync(ListWorkteamsRequest listWorkteamsRequest)` Gets a list of private work teams that you have defined in a region.
`Future<ListWorkteamsResult>`	`listWorkteamsAsync(ListWorkteamsRequest listWorkteamsRequest, AsyncHandler<ListWorkteamsRequest,ListWorkteamsResult> asyncHandler)` Gets a list of private work teams that you have defined in a region.
`Future<PutModelPackageGroupPolicyResult>`	`putModelPackageGroupPolicyAsync(PutModelPackageGroupPolicyRequest putModelPackageGroupPolicyRequest)` Adds a resouce policy to control access to a model group.
`Future<PutModelPackageGroupPolicyResult>`	`putModelPackageGroupPolicyAsync(PutModelPackageGroupPolicyRequest putModelPackageGroupPolicyRequest, AsyncHandler<PutModelPackageGroupPolicyRequest,PutModelPackageGroupPolicyResult> asyncHandler)` Adds a resouce policy to control access to a model group.
`Future<QueryLineageResult>`	`queryLineageAsync(QueryLineageRequest queryLineageRequest)` Use this action to inspect your lineage and discover relationships between entities.
`Future<QueryLineageResult>`	`queryLineageAsync(QueryLineageRequest queryLineageRequest, AsyncHandler<QueryLineageRequest,QueryLineageResult> asyncHandler)` Use this action to inspect your lineage and discover relationships between entities.
`Future<RegisterDevicesResult>`	`registerDevicesAsync(RegisterDevicesRequest registerDevicesRequest)` Register devices.
`Future<RegisterDevicesResult>`	`registerDevicesAsync(RegisterDevicesRequest registerDevicesRequest, AsyncHandler<RegisterDevicesRequest,RegisterDevicesResult> asyncHandler)` Register devices.
`Future<RenderUiTemplateResult>`	`renderUiTemplateAsync(RenderUiTemplateRequest renderUiTemplateRequest)` Renders the UI template so that you can preview the worker's experience.
`Future<RenderUiTemplateResult>`	`renderUiTemplateAsync(RenderUiTemplateRequest renderUiTemplateRequest, AsyncHandler<RenderUiTemplateRequest,RenderUiTemplateResult> asyncHandler)` Renders the UI template so that you can preview the worker's experience.
`Future<RetryPipelineExecutionResult>`	`retryPipelineExecutionAsync(RetryPipelineExecutionRequest retryPipelineExecutionRequest)` Retry the execution of the pipeline.
`Future<RetryPipelineExecutionResult>`	`retryPipelineExecutionAsync(RetryPipelineExecutionRequest retryPipelineExecutionRequest, AsyncHandler<RetryPipelineExecutionRequest,RetryPipelineExecutionResult> asyncHandler)` Retry the execution of the pipeline.
`Future<SearchResult>`	`searchAsync(SearchRequest searchRequest)` Finds Amazon SageMaker resources that match a search query.
`Future<SearchResult>`	`searchAsync(SearchRequest searchRequest, AsyncHandler<SearchRequest,SearchResult> asyncHandler)` Finds Amazon SageMaker resources that match a search query.
`Future<SendPipelineExecutionStepFailureResult>`	`sendPipelineExecutionStepFailureAsync(SendPipelineExecutionStepFailureRequest sendPipelineExecutionStepFailureRequest)` Notifies the pipeline that the execution of a callback step failed, along with a message describing why.
`Future<SendPipelineExecutionStepFailureResult>`	`sendPipelineExecutionStepFailureAsync(SendPipelineExecutionStepFailureRequest sendPipelineExecutionStepFailureRequest, AsyncHandler<SendPipelineExecutionStepFailureRequest,SendPipelineExecutionStepFailureResult> asyncHandler)` Notifies the pipeline that the execution of a callback step failed, along with a message describing why.
`Future<SendPipelineExecutionStepSuccessResult>`	`sendPipelineExecutionStepSuccessAsync(SendPipelineExecutionStepSuccessRequest sendPipelineExecutionStepSuccessRequest)` Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters.
`Future<SendPipelineExecutionStepSuccessResult>`	`sendPipelineExecutionStepSuccessAsync(SendPipelineExecutionStepSuccessRequest sendPipelineExecutionStepSuccessRequest, AsyncHandler<SendPipelineExecutionStepSuccessRequest,SendPipelineExecutionStepSuccessResult> asyncHandler)` Notifies the pipeline that the execution of a callback step succeeded and provides a list of the step's output parameters.
`Future<StartMonitoringScheduleResult>`	`startMonitoringScheduleAsync(StartMonitoringScheduleRequest startMonitoringScheduleRequest)` Starts a previously stopped monitoring schedule.
`Future<StartMonitoringScheduleResult>`	`startMonitoringScheduleAsync(StartMonitoringScheduleRequest startMonitoringScheduleRequest, AsyncHandler<StartMonitoringScheduleRequest,StartMonitoringScheduleResult> asyncHandler)` Starts a previously stopped monitoring schedule.
`Future<StartNotebookInstanceResult>`	`startNotebookInstanceAsync(StartNotebookInstanceRequest startNotebookInstanceRequest)` Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume.
`Future<StartNotebookInstanceResult>`	`startNotebookInstanceAsync(StartNotebookInstanceRequest startNotebookInstanceRequest, AsyncHandler<StartNotebookInstanceRequest,StartNotebookInstanceResult> asyncHandler)` Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume.
`Future<StartPipelineExecutionResult>`	`startPipelineExecutionAsync(StartPipelineExecutionRequest startPipelineExecutionRequest)` Starts a pipeline execution.
`Future<StartPipelineExecutionResult>`	`startPipelineExecutionAsync(StartPipelineExecutionRequest startPipelineExecutionRequest, AsyncHandler<StartPipelineExecutionRequest,StartPipelineExecutionResult> asyncHandler)` Starts a pipeline execution.
`Future<StopAutoMLJobResult>`	`stopAutoMLJobAsync(StopAutoMLJobRequest stopAutoMLJobRequest)` A method for forcing the termination of a running job.
`Future<StopAutoMLJobResult>`	`stopAutoMLJobAsync(StopAutoMLJobRequest stopAutoMLJobRequest, AsyncHandler<StopAutoMLJobRequest,StopAutoMLJobResult> asyncHandler)` A method for forcing the termination of a running job.
`Future<StopCompilationJobResult>`	`stopCompilationJobAsync(StopCompilationJobRequest stopCompilationJobRequest)` Stops a model compilation job.
`Future<StopCompilationJobResult>`	`stopCompilationJobAsync(StopCompilationJobRequest stopCompilationJobRequest, AsyncHandler<StopCompilationJobRequest,StopCompilationJobResult> asyncHandler)` Stops a model compilation job.
`Future<StopEdgePackagingJobResult>`	`stopEdgePackagingJobAsync(StopEdgePackagingJobRequest stopEdgePackagingJobRequest)` Request to stop an edge packaging job.
`Future<StopEdgePackagingJobResult>`	`stopEdgePackagingJobAsync(StopEdgePackagingJobRequest stopEdgePackagingJobRequest, AsyncHandler<StopEdgePackagingJobRequest,StopEdgePackagingJobResult> asyncHandler)` Request to stop an edge packaging job.
`Future<StopHyperParameterTuningJobResult>`	`stopHyperParameterTuningJobAsync(StopHyperParameterTuningJobRequest stopHyperParameterTuningJobRequest)` Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
`Future<StopHyperParameterTuningJobResult>`	`stopHyperParameterTuningJobAsync(StopHyperParameterTuningJobRequest stopHyperParameterTuningJobRequest, AsyncHandler<StopHyperParameterTuningJobRequest,StopHyperParameterTuningJobResult> asyncHandler)` Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.
`Future<StopInferenceRecommendationsJobResult>`	`stopInferenceRecommendationsJobAsync(StopInferenceRecommendationsJobRequest stopInferenceRecommendationsJobRequest)` Stops an Inference Recommender job.
`Future<StopInferenceRecommendationsJobResult>`	`stopInferenceRecommendationsJobAsync(StopInferenceRecommendationsJobRequest stopInferenceRecommendationsJobRequest, AsyncHandler<StopInferenceRecommendationsJobRequest,StopInferenceRecommendationsJobResult> asyncHandler)` Stops an Inference Recommender job.
`Future<StopLabelingJobResult>`	`stopLabelingJobAsync(StopLabelingJobRequest stopLabelingJobRequest)` Stops a running labeling job.
`Future<StopLabelingJobResult>`	`stopLabelingJobAsync(StopLabelingJobRequest stopLabelingJobRequest, AsyncHandler<StopLabelingJobRequest,StopLabelingJobResult> asyncHandler)` Stops a running labeling job.
`Future<StopMonitoringScheduleResult>`	`stopMonitoringScheduleAsync(StopMonitoringScheduleRequest stopMonitoringScheduleRequest)` Stops a previously started monitoring schedule.
`Future<StopMonitoringScheduleResult>`	`stopMonitoringScheduleAsync(StopMonitoringScheduleRequest stopMonitoringScheduleRequest, AsyncHandler<StopMonitoringScheduleRequest,StopMonitoringScheduleResult> asyncHandler)` Stops a previously started monitoring schedule.
`Future<StopNotebookInstanceResult>`	`stopNotebookInstanceAsync(StopNotebookInstanceRequest stopNotebookInstanceRequest)` Terminates the ML compute instance.
`Future<StopNotebookInstanceResult>`	`stopNotebookInstanceAsync(StopNotebookInstanceRequest stopNotebookInstanceRequest, AsyncHandler<StopNotebookInstanceRequest,StopNotebookInstanceResult> asyncHandler)` Terminates the ML compute instance.
`Future<StopPipelineExecutionResult>`	`stopPipelineExecutionAsync(StopPipelineExecutionRequest stopPipelineExecutionRequest)` Stops a pipeline execution.
`Future<StopPipelineExecutionResult>`	`stopPipelineExecutionAsync(StopPipelineExecutionRequest stopPipelineExecutionRequest, AsyncHandler<StopPipelineExecutionRequest,StopPipelineExecutionResult> asyncHandler)` Stops a pipeline execution.
`Future<StopProcessingJobResult>`	`stopProcessingJobAsync(StopProcessingJobRequest stopProcessingJobRequest)` Stops a processing job.
`Future<StopProcessingJobResult>`	`stopProcessingJobAsync(StopProcessingJobRequest stopProcessingJobRequest, AsyncHandler<StopProcessingJobRequest,StopProcessingJobResult> asyncHandler)` Stops a processing job.
`Future<StopTrainingJobResult>`	`stopTrainingJobAsync(StopTrainingJobRequest stopTrainingJobRequest)` Stops a training job.
`Future<StopTrainingJobResult>`	`stopTrainingJobAsync(StopTrainingJobRequest stopTrainingJobRequest, AsyncHandler<StopTrainingJobRequest,StopTrainingJobResult> asyncHandler)` Stops a training job.
`Future<StopTransformJobResult>`	`stopTransformJobAsync(StopTransformJobRequest stopTransformJobRequest)` Stops a batch transform job.
`Future<StopTransformJobResult>`	`stopTransformJobAsync(StopTransformJobRequest stopTransformJobRequest, AsyncHandler<StopTransformJobRequest,StopTransformJobResult> asyncHandler)` Stops a batch transform job.
`Future<UpdateActionResult>`	`updateActionAsync(UpdateActionRequest updateActionRequest)` Updates an action.
`Future<UpdateActionResult>`	`updateActionAsync(UpdateActionRequest updateActionRequest, AsyncHandler<UpdateActionRequest,UpdateActionResult> asyncHandler)` Updates an action.
`Future<UpdateAppImageConfigResult>`	`updateAppImageConfigAsync(UpdateAppImageConfigRequest updateAppImageConfigRequest)` Updates the properties of an AppImageConfig.
`Future<UpdateAppImageConfigResult>`	`updateAppImageConfigAsync(UpdateAppImageConfigRequest updateAppImageConfigRequest, AsyncHandler<UpdateAppImageConfigRequest,UpdateAppImageConfigResult> asyncHandler)` Updates the properties of an AppImageConfig.
`Future<UpdateArtifactResult>`	`updateArtifactAsync(UpdateArtifactRequest updateArtifactRequest)` Updates an artifact.
`Future<UpdateArtifactResult>`	`updateArtifactAsync(UpdateArtifactRequest updateArtifactRequest, AsyncHandler<UpdateArtifactRequest,UpdateArtifactResult> asyncHandler)` Updates an artifact.
`Future<UpdateCodeRepositoryResult>`	`updateCodeRepositoryAsync(UpdateCodeRepositoryRequest updateCodeRepositoryRequest)` Updates the specified Git repository with the specified values.
`Future<UpdateCodeRepositoryResult>`	`updateCodeRepositoryAsync(UpdateCodeRepositoryRequest updateCodeRepositoryRequest, AsyncHandler<UpdateCodeRepositoryRequest,UpdateCodeRepositoryResult> asyncHandler)` Updates the specified Git repository with the specified values.
`Future<UpdateContextResult>`	`updateContextAsync(UpdateContextRequest updateContextRequest)` Updates a context.
`Future<UpdateContextResult>`	`updateContextAsync(UpdateContextRequest updateContextRequest, AsyncHandler<UpdateContextRequest,UpdateContextResult> asyncHandler)` Updates a context.
`Future<UpdateDeviceFleetResult>`	`updateDeviceFleetAsync(UpdateDeviceFleetRequest updateDeviceFleetRequest)` Updates a fleet of devices.
`Future<UpdateDeviceFleetResult>`	`updateDeviceFleetAsync(UpdateDeviceFleetRequest updateDeviceFleetRequest, AsyncHandler<UpdateDeviceFleetRequest,UpdateDeviceFleetResult> asyncHandler)` Updates a fleet of devices.
`Future<UpdateDevicesResult>`	`updateDevicesAsync(UpdateDevicesRequest updateDevicesRequest)` Updates one or more devices in a fleet.
`Future<UpdateDevicesResult>`	`updateDevicesAsync(UpdateDevicesRequest updateDevicesRequest, AsyncHandler<UpdateDevicesRequest,UpdateDevicesResult> asyncHandler)` Updates one or more devices in a fleet.
`Future<UpdateDomainResult>`	`updateDomainAsync(UpdateDomainRequest updateDomainRequest)` Updates the default settings for new user profiles in the domain.
`Future<UpdateDomainResult>`	`updateDomainAsync(UpdateDomainRequest updateDomainRequest, AsyncHandler<UpdateDomainRequest,UpdateDomainResult> asyncHandler)` Updates the default settings for new user profiles in the domain.
`Future<UpdateEndpointResult>`	`updateEndpointAsync(UpdateEndpointRequest updateEndpointRequest)` Deploys the new `EndpointConfig` specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous `EndpointConfig` (there is no availability loss).
`Future<UpdateEndpointResult>`	`updateEndpointAsync(UpdateEndpointRequest updateEndpointRequest, AsyncHandler<UpdateEndpointRequest,UpdateEndpointResult> asyncHandler)` Deploys the new `EndpointConfig` specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous `EndpointConfig` (there is no availability loss).
`Future<UpdateEndpointWeightsAndCapacitiesResult>`	`updateEndpointWeightsAndCapacitiesAsync(UpdateEndpointWeightsAndCapacitiesRequest updateEndpointWeightsAndCapacitiesRequest)` Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint.
`Future<UpdateEndpointWeightsAndCapacitiesResult>`	`updateEndpointWeightsAndCapacitiesAsync(UpdateEndpointWeightsAndCapacitiesRequest updateEndpointWeightsAndCapacitiesRequest, AsyncHandler<UpdateEndpointWeightsAndCapacitiesRequest,UpdateEndpointWeightsAndCapacitiesResult> asyncHandler)` Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint.
`Future<UpdateExperimentResult>`	`updateExperimentAsync(UpdateExperimentRequest updateExperimentRequest)` Adds, updates, or removes the description of an experiment.
`Future<UpdateExperimentResult>`	`updateExperimentAsync(UpdateExperimentRequest updateExperimentRequest, AsyncHandler<UpdateExperimentRequest,UpdateExperimentResult> asyncHandler)` Adds, updates, or removes the description of an experiment.
`Future<UpdateImageResult>`	`updateImageAsync(UpdateImageRequest updateImageRequest)` Updates the properties of a SageMaker image.
`Future<UpdateImageResult>`	`updateImageAsync(UpdateImageRequest updateImageRequest, AsyncHandler<UpdateImageRequest,UpdateImageResult> asyncHandler)` Updates the properties of a SageMaker image.
`Future<UpdateModelPackageResult>`	`updateModelPackageAsync(UpdateModelPackageRequest updateModelPackageRequest)` Updates a versioned model.
`Future<UpdateModelPackageResult>`	`updateModelPackageAsync(UpdateModelPackageRequest updateModelPackageRequest, AsyncHandler<UpdateModelPackageRequest,UpdateModelPackageResult> asyncHandler)` Updates a versioned model.
`Future<UpdateMonitoringScheduleResult>`	`updateMonitoringScheduleAsync(UpdateMonitoringScheduleRequest updateMonitoringScheduleRequest)` Updates a previously created schedule.
`Future<UpdateMonitoringScheduleResult>`	`updateMonitoringScheduleAsync(UpdateMonitoringScheduleRequest updateMonitoringScheduleRequest, AsyncHandler<UpdateMonitoringScheduleRequest,UpdateMonitoringScheduleResult> asyncHandler)` Updates a previously created schedule.
`Future<UpdateNotebookInstanceResult>`	`updateNotebookInstanceAsync(UpdateNotebookInstanceRequest updateNotebookInstanceRequest)` Updates a notebook instance.
`Future<UpdateNotebookInstanceResult>`	`updateNotebookInstanceAsync(UpdateNotebookInstanceRequest updateNotebookInstanceRequest, AsyncHandler<UpdateNotebookInstanceRequest,UpdateNotebookInstanceResult> asyncHandler)` Updates a notebook instance.
`Future<UpdateNotebookInstanceLifecycleConfigResult>`	`updateNotebookInstanceLifecycleConfigAsync(UpdateNotebookInstanceLifecycleConfigRequest updateNotebookInstanceLifecycleConfigRequest)` Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
`Future<UpdateNotebookInstanceLifecycleConfigResult>`	`updateNotebookInstanceLifecycleConfigAsync(UpdateNotebookInstanceLifecycleConfigRequest updateNotebookInstanceLifecycleConfigRequest, AsyncHandler<UpdateNotebookInstanceLifecycleConfigRequest,UpdateNotebookInstanceLifecycleConfigResult> asyncHandler)` Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.
`Future<UpdatePipelineResult>`	`updatePipelineAsync(UpdatePipelineRequest updatePipelineRequest)` Updates a pipeline.
`Future<UpdatePipelineResult>`	`updatePipelineAsync(UpdatePipelineRequest updatePipelineRequest, AsyncHandler<UpdatePipelineRequest,UpdatePipelineResult> asyncHandler)` Updates a pipeline.
`Future<UpdatePipelineExecutionResult>`	`updatePipelineExecutionAsync(UpdatePipelineExecutionRequest updatePipelineExecutionRequest)` Updates a pipeline execution.
`Future<UpdatePipelineExecutionResult>`	`updatePipelineExecutionAsync(UpdatePipelineExecutionRequest updatePipelineExecutionRequest, AsyncHandler<UpdatePipelineExecutionRequest,UpdatePipelineExecutionResult> asyncHandler)` Updates a pipeline execution.
`Future<UpdateProjectResult>`	`updateProjectAsync(UpdateProjectRequest updateProjectRequest)` Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
`Future<UpdateProjectResult>`	`updateProjectAsync(UpdateProjectRequest updateProjectRequest, AsyncHandler<UpdateProjectRequest,UpdateProjectResult> asyncHandler)` Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.
`Future<UpdateTrainingJobResult>`	`updateTrainingJobAsync(UpdateTrainingJobRequest updateTrainingJobRequest)` Update a model training job to request a new Debugger profiling configuration.
`Future<UpdateTrainingJobResult>`	`updateTrainingJobAsync(UpdateTrainingJobRequest updateTrainingJobRequest, AsyncHandler<UpdateTrainingJobRequest,UpdateTrainingJobResult> asyncHandler)` Update a model training job to request a new Debugger profiling configuration.
`Future<UpdateTrialResult>`	`updateTrialAsync(UpdateTrialRequest updateTrialRequest)` Updates the display name of a trial.
`Future<UpdateTrialResult>`	`updateTrialAsync(UpdateTrialRequest updateTrialRequest, AsyncHandler<UpdateTrialRequest,UpdateTrialResult> asyncHandler)` Updates the display name of a trial.
`Future<UpdateTrialComponentResult>`	`updateTrialComponentAsync(UpdateTrialComponentRequest updateTrialComponentRequest)` Updates one or more properties of a trial component.
`Future<UpdateTrialComponentResult>`	`updateTrialComponentAsync(UpdateTrialComponentRequest updateTrialComponentRequest, AsyncHandler<UpdateTrialComponentRequest,UpdateTrialComponentResult> asyncHandler)` Updates one or more properties of a trial component.
`Future<UpdateUserProfileResult>`	`updateUserProfileAsync(UpdateUserProfileRequest updateUserProfileRequest)` Updates a user profile.
`Future<UpdateUserProfileResult>`	`updateUserProfileAsync(UpdateUserProfileRequest updateUserProfileRequest, AsyncHandler<UpdateUserProfileRequest,UpdateUserProfileResult> asyncHandler)` Updates a user profile.
`Future<UpdateWorkforceResult>`	`updateWorkforceAsync(UpdateWorkforceRequest updateWorkforceRequest)` Use this operation to update your workforce.
`Future<UpdateWorkforceResult>`	`updateWorkforceAsync(UpdateWorkforceRequest updateWorkforceRequest, AsyncHandler<UpdateWorkforceRequest,UpdateWorkforceResult> asyncHandler)` Use this operation to update your workforce.
`Future<UpdateWorkteamResult>`	`updateWorkteamAsync(UpdateWorkteamRequest updateWorkteamRequest)` Updates an existing work team with new member definitions or description.
`Future<UpdateWorkteamResult>`	`updateWorkteamAsync(UpdateWorkteamRequest updateWorkteamRequest, AsyncHandler<UpdateWorkteamRequest,UpdateWorkteamResult> asyncHandler)` Updates an existing work team with new member definitions or description.

Methods inherited from interface com.amazonaws.services.sagemaker.AmazonSageMaker
addAssociation, addTags, associateTrialComponent, batchDescribeModelPackage, createAction, createAlgorithm, createApp, createAppImageConfig, createArtifact, createAutoMLJob, createCodeRepository, createCompilationJob, createContext, createDataQualityJobDefinition, createDeviceFleet, createDomain, createEdgePackagingJob, createEndpoint, createEndpointConfig, createExperiment, createFeatureGroup, createFlowDefinition, createHumanTaskUi, createHyperParameterTuningJob, createImage, createImageVersion, createInferenceRecommendationsJob, createLabelingJob, createModel, createModelBiasJobDefinition, createModelExplainabilityJobDefinition, createModelPackage, createModelPackageGroup, createModelQualityJobDefinition, createMonitoringSchedule, createNotebookInstance, createNotebookInstanceLifecycleConfig, createPipeline, createPresignedDomainUrl, createPresignedNotebookInstanceUrl, createProcessingJob, createProject, createStudioLifecycleConfig, createTrainingJob, createTransformJob, createTrial, createTrialComponent, createUserProfile, createWorkforce, createWorkteam, deleteAction, deleteAlgorithm, deleteApp, deleteAppImageConfig, deleteArtifact, deleteAssociation, deleteCodeRepository, deleteContext, deleteDataQualityJobDefinition, deleteDeviceFleet, deleteDomain, deleteEndpoint, deleteEndpointConfig, deleteExperiment, deleteFeatureGroup, deleteFlowDefinition, deleteHumanTaskUi, deleteImage, deleteImageVersion, deleteModel, deleteModelBiasJobDefinition, deleteModelExplainabilityJobDefinition, deleteModelPackage, deleteModelPackageGroup, deleteModelPackageGroupPolicy, deleteModelQualityJobDefinition, deleteMonitoringSchedule, deleteNotebookInstance, deleteNotebookInstanceLifecycleConfig, deletePipeline, deleteProject, deleteStudioLifecycleConfig, deleteTags, deleteTrial, deleteTrialComponent, deleteUserProfile, deleteWorkforce, deleteWorkteam, deregisterDevices, describeAction, describeAlgorithm, describeApp, describeAppImageConfig, describeArtifact, describeAutoMLJob, describeCodeRepository, describeCompilationJob, describeContext, describeDataQualityJobDefinition, describeDevice, describeDeviceFleet, describeDomain, describeEdgePackagingJob, describeEndpoint, describeEndpointConfig, describeExperiment, describeFeatureGroup, describeFlowDefinition, describeHumanTaskUi, describeHyperParameterTuningJob, describeImage, describeImageVersion, describeInferenceRecommendationsJob, describeLabelingJob, describeLineageGroup, describeModel, describeModelBiasJobDefinition, describeModelExplainabilityJobDefinition, describeModelPackage, describeModelPackageGroup, describeModelQualityJobDefinition, describeMonitoringSchedule, describeNotebookInstance, describeNotebookInstanceLifecycleConfig, describePipeline, describePipelineDefinitionForExecution, describePipelineExecution, describeProcessingJob, describeProject, describeStudioLifecycleConfig, describeSubscribedWorkteam, describeTrainingJob, describeTransformJob, describeTrial, describeTrialComponent, describeUserProfile, describeWorkforce, describeWorkteam, disableSagemakerServicecatalogPortfolio, disassociateTrialComponent, enableSagemakerServicecatalogPortfolio, getCachedResponseMetadata, getDeviceFleetReport, getLineageGroupPolicy, getModelPackageGroupPolicy, getSagemakerServicecatalogPortfolioStatus, getSearchSuggestions, listActions, listAlgorithms, listAppImageConfigs, listApps, listArtifacts, listAssociations, listAutoMLJobs, listCandidatesForAutoMLJob, listCodeRepositories, listCompilationJobs, listContexts, listDataQualityJobDefinitions, listDeviceFleets, listDevices, listDomains, listEdgePackagingJobs, listEndpointConfigs, listEndpoints, listExperiments, listFeatureGroups, listFlowDefinitions, listHumanTaskUis, listHyperParameterTuningJobs, listImages, listImageVersions, listInferenceRecommendationsJobs, listLabelingJobs, listLabelingJobsForWorkteam, listLineageGroups, listModelBiasJobDefinitions, listModelExplainabilityJobDefinitions, listModelMetadata, listModelPackageGroups, listModelPackages, listModelQualityJobDefinitions, listModels, listMonitoringExecutions, listMonitoringSchedules, listNotebookInstanceLifecycleConfigs, listNotebookInstances, listPipelineExecutions, listPipelineExecutionSteps, listPipelineParametersForExecution, listPipelines, listProcessingJobs, listProjects, listStudioLifecycleConfigs, listSubscribedWorkteams, listTags, listTrainingJobs, listTrainingJobsForHyperParameterTuningJob, listTransformJobs, listTrialComponents, listTrials, listUserProfiles, listWorkforces, listWorkteams, putModelPackageGroupPolicy, queryLineage, registerDevices, renderUiTemplate, retryPipelineExecution, search, sendPipelineExecutionStepFailure, sendPipelineExecutionStepSuccess, shutdown, startMonitoringSchedule, startNotebookInstance, startPipelineExecution, stopAutoMLJob, stopCompilationJob, stopEdgePackagingJob, stopHyperParameterTuningJob, stopInferenceRecommendationsJob, stopLabelingJob, stopMonitoringSchedule, stopNotebookInstance, stopPipelineExecution, stopProcessingJob, stopTrainingJob, stopTransformJob, updateAction, updateAppImageConfig, updateArtifact, updateCodeRepository, updateContext, updateDeviceFleet, updateDevices, updateDomain, updateEndpoint, updateEndpointWeightsAndCapacities, updateExperiment, updateImage, updateModelPackage, updateMonitoringSchedule, updateNotebookInstance, updateNotebookInstanceLifecycleConfig, updatePipeline, updatePipelineExecution, updateProject, updateTrainingJob, updateTrial, updateTrialComponent, updateUserProfile, updateWorkforce, updateWorkteam, waiters

- Method Detail
  - addAssociationAsync
```
Future<AddAssociationResult> addAssociationAsync(AddAssociationRequest addAssociationRequest)
```
    Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking.
    
    Parameters:
    
    addAssociationRequest -
    
    Returns:
    
    A Java Future containing the result of the AddAssociation operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - addAssociationAsync
```
Future<AddAssociationResult> addAssociationAsync(AddAssociationRequest addAssociationRequest,
                                                 AsyncHandler<AddAssociationRequest,AddAssociationResult> asyncHandler)
```
    Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking.
    
    Parameters:
    
    addAssociationRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the AddAssociation operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - addTagsAsync
```
Future<AddTagsResult> addTagsAsync(AddTagsRequest addTagsRequest)
```
    Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
    
    Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
    
    Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
    
    Tags that you add to a SageMaker Studio Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags parameter of CreateDomain or CreateUserProfile.
    
    Parameters:
    
    addTagsRequest -
    
    Returns:
    
    A Java Future containing the result of the AddTags operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - addTagsAsync
```
Future<AddTagsResult> addTagsAsync(AddTagsRequest addTagsRequest,
                                   AsyncHandler<AddTagsRequest,AddTagsResult> asyncHandler)
```
    Adds or overwrites one or more tags for the specified SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints.
    
    Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see Amazon Web Services Tagging Strategies.
    
    Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob
    
    Tags that you add to a SageMaker Studio Domain or User Profile by calling this API are also added to any Apps that the Domain or User Profile launches after you call this API, but not to Apps that the Domain or User Profile launched before you called this API. To make sure that the tags associated with a Domain or User Profile are also added to all Apps that the Domain or User Profile launches, add the tags when you first create the Domain or User Profile by specifying them in the Tags parameter of CreateDomain or CreateUserProfile.
    
    Parameters:
    
    addTagsRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the AddTags operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - associateTrialComponentAsync
```
Future<AssociateTrialComponentResult> associateTrialComponentAsync(AssociateTrialComponentRequest associateTrialComponentRequest)
```
    Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
    
    Parameters:
    
    associateTrialComponentRequest -
    
    Returns:
    
    A Java Future containing the result of the AssociateTrialComponent operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - associateTrialComponentAsync
```
Future<AssociateTrialComponentResult> associateTrialComponentAsync(AssociateTrialComponentRequest associateTrialComponentRequest,
                                                                   AsyncHandler<AssociateTrialComponentRequest,AssociateTrialComponentResult> asyncHandler)
```
    Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.
    
    Parameters:
    
    associateTrialComponentRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the AssociateTrialComponent operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - batchDescribeModelPackageAsync
```
Future<BatchDescribeModelPackageResult> batchDescribeModelPackageAsync(BatchDescribeModelPackageRequest batchDescribeModelPackageRequest)
```
    This action batch describes a list of versioned model packages
    
    Parameters:
    
    batchDescribeModelPackageRequest -
    
    Returns:
    
    A Java Future containing the result of the BatchDescribeModelPackage operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - batchDescribeModelPackageAsync
```
Future<BatchDescribeModelPackageResult> batchDescribeModelPackageAsync(BatchDescribeModelPackageRequest batchDescribeModelPackageRequest,
                                                                       AsyncHandler<BatchDescribeModelPackageRequest,BatchDescribeModelPackageResult> asyncHandler)
```
    This action batch describes a list of versioned model packages
    
    Parameters:
    
    batchDescribeModelPackageRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the BatchDescribeModelPackage operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createActionAsync
```
Future<CreateActionResult> createActionAsync(CreateActionRequest createActionRequest)
```
    Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking.
    
    Parameters:
    
    createActionRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateAction operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createActionAsync
```
Future<CreateActionResult> createActionAsync(CreateActionRequest createActionRequest,
                                             AsyncHandler<CreateActionRequest,CreateActionResult> asyncHandler)
```
    Creates an action. An action is a lineage tracking entity that represents an action or activity. For example, a model deployment or an HPO job. Generally, an action involves at least one input or output artifact. For more information, see Amazon SageMaker ML Lineage Tracking.
    
    Parameters:
    
    createActionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateAction operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createAlgorithmAsync
```
Future<CreateAlgorithmResult> createAlgorithmAsync(CreateAlgorithmRequest createAlgorithmRequest)
```
    Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
    
    Parameters:
    
    createAlgorithmRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateAlgorithm operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createAlgorithmAsync
```
Future<CreateAlgorithmResult> createAlgorithmAsync(CreateAlgorithmRequest createAlgorithmRequest,
                                                   AsyncHandler<CreateAlgorithmRequest,CreateAlgorithmResult> asyncHandler)
```
    Create a machine learning algorithm that you can use in SageMaker and list in the Amazon Web Services Marketplace.
    
    Parameters:
    
    createAlgorithmRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateAlgorithm operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createAppAsync
```
Future<CreateAppResult> createAppAsync(CreateAppRequest createAppRequest)
```
    Creates a running app for the specified UserProfile. Supported apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
    
    Parameters:
    
    createAppRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateApp operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createAppAsync
```
Future<CreateAppResult> createAppAsync(CreateAppRequest createAppRequest,
                                       AsyncHandler<CreateAppRequest,CreateAppResult> asyncHandler)
```
    Creates a running app for the specified UserProfile. Supported apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
    
    Parameters:
    
    createAppRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateApp operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createAppImageConfigAsync
```
Future<CreateAppImageConfigResult> createAppImageConfigAsync(CreateAppImageConfigRequest createAppImageConfigRequest)
```
    Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.
    
    Parameters:
    
    createAppImageConfigRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateAppImageConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createAppImageConfigAsync
```
Future<CreateAppImageConfigResult> createAppImageConfigAsync(CreateAppImageConfigRequest createAppImageConfigRequest,
                                                             AsyncHandler<CreateAppImageConfigRequest,CreateAppImageConfigResult> asyncHandler)
```
    Creates a configuration for running a SageMaker image as a KernelGateway app. The configuration specifies the Amazon Elastic File System (EFS) storage volume on the image, and a list of the kernels in the image.
    
    Parameters:
    
    createAppImageConfigRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateAppImageConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createArtifactAsync
```
Future<CreateArtifactResult> createArtifactAsync(CreateArtifactRequest createArtifactRequest)
```
    Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking.
    
    Parameters:
    
    createArtifactRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateArtifact operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createArtifactAsync
```
Future<CreateArtifactResult> createArtifactAsync(CreateArtifactRequest createArtifactRequest,
                                                 AsyncHandler<CreateArtifactRequest,CreateArtifactResult> asyncHandler)
```
    Creates an artifact. An artifact is a lineage tracking entity that represents a URI addressable object or data. Some examples are the S3 URI of a dataset and the ECR registry path of an image. For more information, see Amazon SageMaker ML Lineage Tracking.
    
    Parameters:
    
    createArtifactRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateArtifact operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createAutoMLJobAsync
```
Future<CreateAutoMLJobResult> createAutoMLJobAsync(CreateAutoMLJobRequest createAutoMLJobRequest)
```
    Creates an Autopilot job.
    
    Find the best-performing model after you run an Autopilot job by calling .
    
    For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.
    
    Parameters:
    
    createAutoMLJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateAutoMLJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createAutoMLJobAsync
```
Future<CreateAutoMLJobResult> createAutoMLJobAsync(CreateAutoMLJobRequest createAutoMLJobRequest,
                                                   AsyncHandler<CreateAutoMLJobRequest,CreateAutoMLJobResult> asyncHandler)
```
    Creates an Autopilot job.
    
    Find the best-performing model after you run an Autopilot job by calling .
    
    For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot.
    
    Parameters:
    
    createAutoMLJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateAutoMLJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createCodeRepositoryAsync
```
Future<CreateCodeRepositoryResult> createCodeRepositoryAsync(CreateCodeRepositoryRequest createCodeRepositoryRequest)
```
    Creates a Git repository as a resource in your SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
    
    The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.
    
    Parameters:
    
    createCodeRepositoryRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateCodeRepository operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createCodeRepositoryAsync
```
Future<CreateCodeRepositoryResult> createCodeRepositoryAsync(CreateCodeRepositoryRequest createCodeRepositoryRequest,
                                                             AsyncHandler<CreateCodeRepositoryRequest,CreateCodeRepositoryResult> asyncHandler)
```
    Creates a Git repository as a resource in your SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with.
    
    The repository can be hosted either in Amazon Web Services CodeCommit or in any other Git repository.
    
    Parameters:
    
    createCodeRepositoryRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateCodeRepository operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createCompilationJobAsync
```
Future<CreateCompilationJobResult> createCompilationJobAsync(CreateCompilationJobRequest createCompilationJobRequest)
```
    Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
    
    If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
    
    In the request body, you provide the following:
    - A name for the compilation job
    - Information about the input model artifacts
    - The output location for the compiled model and the device (target) that the model runs on
    - The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
    You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job.
    
    To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
    Parameters:
    
    createCompilationJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateCompilationJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createCompilationJobAsync
```
Future<CreateCompilationJobResult> createCompilationJobAsync(CreateCompilationJobRequest createCompilationJobRequest,
                                                             AsyncHandler<CreateCompilationJobRequest,CreateCompilationJobResult> asyncHandler)
```
    Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
    
    If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
    
    In the request body, you provide the following:
    - A name for the compilation job
    - Information about the input model artifacts
    - The output location for the compiled model and the device (target) that the model runs on
    - The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
    You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job.
    
    To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
    Parameters:
    
    createCompilationJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateCompilationJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createContextAsync
```
Future<CreateContextResult> createContextAsync(CreateContextRequest createContextRequest)
```
    Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
    
    Parameters:
    
    createContextRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateContext operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createContextAsync
```
Future<CreateContextResult> createContextAsync(CreateContextRequest createContextRequest,
                                               AsyncHandler<CreateContextRequest,CreateContextResult> asyncHandler)
```
    Creates a context. A context is a lineage tracking entity that represents a logical grouping of other tracking or experiment entities. Some examples are an endpoint and a model package. For more information, see Amazon SageMaker ML Lineage Tracking.
    
    Parameters:
    
    createContextRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateContext operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDataQualityJobDefinitionAsync
```
Future<CreateDataQualityJobDefinitionResult> createDataQualityJobDefinitionAsync(CreateDataQualityJobDefinitionRequest createDataQualityJobDefinitionRequest)
```
    Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
    
    Parameters:
    
    createDataQualityJobDefinitionRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateDataQualityJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDataQualityJobDefinitionAsync
```
Future<CreateDataQualityJobDefinitionResult> createDataQualityJobDefinitionAsync(CreateDataQualityJobDefinitionRequest createDataQualityJobDefinitionRequest,
                                                                                 AsyncHandler<CreateDataQualityJobDefinitionRequest,CreateDataQualityJobDefinitionResult> asyncHandler)
```
    Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
    
    Parameters:
    
    createDataQualityJobDefinitionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateDataQualityJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDeviceFleetAsync
```
Future<CreateDeviceFleetResult> createDeviceFleetAsync(CreateDeviceFleetRequest createDeviceFleetRequest)
```
    Creates a device fleet.
    
    Parameters:
    
    createDeviceFleetRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateDeviceFleet operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDeviceFleetAsync
```
Future<CreateDeviceFleetResult> createDeviceFleetAsync(CreateDeviceFleetRequest createDeviceFleetRequest,
                                                       AsyncHandler<CreateDeviceFleetRequest,CreateDeviceFleetResult> asyncHandler)
```
    Creates a device fleet.
    
    Parameters:
    
    createDeviceFleetRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateDeviceFleet operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDomainAsync
```
Future<CreateDomainResult> createDomainAsync(CreateDomainRequest createDomainRequest)
```
    Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An Amazon Web Services account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other.
    
    EFS storage
    
    When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
    
    SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
    
    VPC configuration
    
    All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:
    - PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
    - VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
      
      When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
    NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a SageMaker Studio app successfully.
    
    For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC.
    Parameters:
    
    createDomainRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateDomain operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createDomainAsync
```
Future<CreateDomainResult> createDomainAsync(CreateDomainRequest createDomainRequest,
                                             AsyncHandler<CreateDomainRequest,CreateDomainResult> asyncHandler)
```
    Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An Amazon Web Services account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other.
    
    EFS storage
    
    When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files.
    
    SageMaker uses the Amazon Web Services Key Management Service (Amazon Web Services KMS) to encrypt the EFS volume attached to the domain with an Amazon Web Services managed key by default. For more control, you can specify a customer managed key. For more information, see Protect Data at Rest Using Encryption.
    
    VPC configuration
    
    All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:
    - PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.
    - VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway.
      
      When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.
    NFS traffic over TCP on port 2049 needs to be allowed in both inbound and outbound rules in order to launch a SageMaker Studio app successfully.
    
    For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC.
    Parameters:
    
    createDomainRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateDomain operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createEdgePackagingJobAsync
```
Future<CreateEdgePackagingJobResult> createEdgePackagingJobAsync(CreateEdgePackagingJobRequest createEdgePackagingJobRequest)
```
    Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.
    
    Parameters:
    
    createEdgePackagingJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateEdgePackagingJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createEdgePackagingJobAsync
```
Future<CreateEdgePackagingJobResult> createEdgePackagingJobAsync(CreateEdgePackagingJobRequest createEdgePackagingJobRequest,
                                                                 AsyncHandler<CreateEdgePackagingJobRequest,CreateEdgePackagingJobResult> asyncHandler)
```
    Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.
    
    Parameters:
    
    createEdgePackagingJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateEdgePackagingJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createEndpointAsync
```
Future<CreateEndpointResult> createEndpointAsync(CreateEndpointRequest createEndpointRequest)
```
    Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
    
    Use this API to deploy models using SageMaker hosting services.
    
    For an example that calls this method when deploying a model to SageMaker hosting services, see the Create Endpoint example notebook.
    
    You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
    
    The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account.
    
    When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
    
    When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
    
    When SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
    
    If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your IAM user account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
    To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
    
    Option 1: For a full SageMaker access, search and attach the AmazonSageMakerFullAccess policy.
    
    Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
    
    "Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
    
    "Resource": [
    
    "arn:aws:sagemaker:region:account-id:endpoint/endpointName"
    
    "arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
    
    ]
    
    For more information, see SageMaker API Permissions: Actions, Permissions, and Resources Reference.
    Parameters:
    
    createEndpointRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateEndpoint operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createEndpointAsync
```
Future<CreateEndpointResult> createEndpointAsync(CreateEndpointRequest createEndpointRequest,
                                                 AsyncHandler<CreateEndpointRequest,CreateEndpointResult> asyncHandler)
```
    Creates an endpoint using the endpoint configuration specified in the request. SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.
    
    Use this API to deploy models using SageMaker hosting services.
    
    For an example that calls this method when deploying a model to SageMaker hosting services, see the Create Endpoint example notebook.
    
    You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig.
    
    The endpoint name must be unique within an Amazon Web Services Region in your Amazon Web Services account.
    
    When it receives the request, SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.
    
    When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
    
    When SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API.
    
    If any of the models hosted at this endpoint get model data from an Amazon S3 location, SageMaker uses Amazon Web Services Security Token Service to download model artifacts from the S3 path you provided. Amazon Web Services STS is activated in your IAM user account by default. If you previously deactivated Amazon Web Services STS for a region, you need to reactivate Amazon Web Services STS for that region. For more information, see Activating and Deactivating Amazon Web Services STS in an Amazon Web Services Region in the Amazon Web Services Identity and Access Management User Guide.
    To add the IAM role policies for using this API operation, go to the IAM console, and choose Roles in the left navigation pane. Search the IAM role that you want to grant access to use the CreateEndpoint and CreateEndpointConfig API operations, add the following policies to the role.
    
    Option 1: For a full SageMaker access, search and attach the AmazonSageMakerFullAccess policy.
    
    Option 2: For granting a limited access to an IAM role, paste the following Action elements manually into the JSON file of the IAM role:
    
    "Action": ["sagemaker:CreateEndpoint", "sagemaker:CreateEndpointConfig"]
    
    "Resource": [
    
    "arn:aws:sagemaker:region:account-id:endpoint/endpointName"
    
    "arn:aws:sagemaker:region:account-id:endpoint-config/endpointConfigName"
    
    ]
    
    For more information, see SageMaker API Permissions: Actions, Permissions, and Resources Reference.
    Parameters:
    
    createEndpointRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateEndpoint operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createEndpointConfigAsync
```
Future<CreateEndpointConfigResult> createEndpointConfigAsync(CreateEndpointConfigRequest createEndpointConfigRequest)
```
    Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
    
    Use this API if you want to use SageMaker hosting services to deploy models into production.
    
    In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
    
    If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
    
    When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
    
    Parameters:
    
    createEndpointConfigRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateEndpointConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createEndpointConfigAsync
```
Future<CreateEndpointConfigResult> createEndpointConfigAsync(CreateEndpointConfigRequest createEndpointConfigRequest,
                                                             AsyncHandler<CreateEndpointConfigRequest,CreateEndpointConfigResult> asyncHandler)
```
    Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.
    
    Use this API if you want to use SageMaker hosting services to deploy models into production.
    
    In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.
    
    If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
    
    When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.
    
    Parameters:
    
    createEndpointConfigRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateEndpointConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createExperimentAsync
```
Future<CreateExperimentResult> createExperimentAsync(CreateExperimentRequest createExperimentRequest)
```
    Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
    
    The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
    
    When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
    
    You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
    
    To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.
    
    To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
    
    Parameters:
    
    createExperimentRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateExperiment operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createExperimentAsync
```
Future<CreateExperimentResult> createExperimentAsync(CreateExperimentRequest createExperimentRequest,
                                                     AsyncHandler<CreateExperimentRequest,CreateExperimentResult> asyncHandler)
```
    Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
    
    The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
    
    When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
    
    You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
    
    To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API.
    
    To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
    
    Parameters:
    
    createExperimentRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateExperiment operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createFeatureGroupAsync
```
Future<CreateFeatureGroupResult> createFeatureGroupAsync(CreateFeatureGroupRequest createFeatureGroupRequest)
```
    Create a new FeatureGroup. A FeatureGroup is a group of Features defined in the FeatureStore to describe a Record.
    
    The FeatureGroup defines the schema and features contained in the FeatureGroup. A FeatureGroup definition is composed of a list of Features, a RecordIdentifierFeatureName, an EventTimeFeatureName and configurations for its OnlineStore and OfflineStore. Check Amazon Web Services service quotas to see the FeatureGroups quota for your Amazon Web Services account.
    
    You must include at least one of OnlineStoreConfig and OfflineStoreConfig to create a FeatureGroup.
    
    Parameters:
    
    createFeatureGroupRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateFeatureGroup operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createFeatureGroupAsync
```
Future<CreateFeatureGroupResult> createFeatureGroupAsync(CreateFeatureGroupRequest createFeatureGroupRequest,
                                                         AsyncHandler<CreateFeatureGroupRequest,CreateFeatureGroupResult> asyncHandler)
```
    Create a new FeatureGroup. A FeatureGroup is a group of Features defined in the FeatureStore to describe a Record.
    
    The FeatureGroup defines the schema and features contained in the FeatureGroup. A FeatureGroup definition is composed of a list of Features, a RecordIdentifierFeatureName, an EventTimeFeatureName and configurations for its OnlineStore and OfflineStore. Check Amazon Web Services service quotas to see the FeatureGroups quota for your Amazon Web Services account.
    
    You must include at least one of OnlineStoreConfig and OfflineStoreConfig to create a FeatureGroup.
    
    Parameters:
    
    createFeatureGroupRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateFeatureGroup operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createFlowDefinitionAsync
```
Future<CreateFlowDefinitionResult> createFlowDefinitionAsync(CreateFlowDefinitionRequest createFlowDefinitionRequest)
```
    Creates a flow definition.
    
    Parameters:
    
    createFlowDefinitionRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateFlowDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createFlowDefinitionAsync
```
Future<CreateFlowDefinitionResult> createFlowDefinitionAsync(CreateFlowDefinitionRequest createFlowDefinitionRequest,
                                                             AsyncHandler<CreateFlowDefinitionRequest,CreateFlowDefinitionResult> asyncHandler)
```
    Creates a flow definition.
    
    Parameters:
    
    createFlowDefinitionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateFlowDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createHumanTaskUiAsync
```
Future<CreateHumanTaskUiResult> createHumanTaskUiAsync(CreateHumanTaskUiRequest createHumanTaskUiRequest)
```
    Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.
    
    Parameters:
    
    createHumanTaskUiRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateHumanTaskUi operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createHumanTaskUiAsync
```
Future<CreateHumanTaskUiResult> createHumanTaskUiAsync(CreateHumanTaskUiRequest createHumanTaskUiRequest,
                                                       AsyncHandler<CreateHumanTaskUiRequest,CreateHumanTaskUiResult> asyncHandler)
```
    Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.
    
    Parameters:
    
    createHumanTaskUiRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateHumanTaskUi operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createHyperParameterTuningJobAsync
```
Future<CreateHyperParameterTuningJobResult> createHyperParameterTuningJobAsync(CreateHyperParameterTuningJobRequest createHyperParameterTuningJobRequest)
```
    Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
    
    Parameters:
    
    createHyperParameterTuningJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateHyperParameterTuningJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createHyperParameterTuningJobAsync
```
Future<CreateHyperParameterTuningJobResult> createHyperParameterTuningJobAsync(CreateHyperParameterTuningJobRequest createHyperParameterTuningJobRequest,
                                                                               AsyncHandler<CreateHyperParameterTuningJobRequest,CreateHyperParameterTuningJobResult> asyncHandler)
```
    Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.
    
    Parameters:
    
    createHyperParameterTuningJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateHyperParameterTuningJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createImageAsync
```
Future<CreateImageResult> createImageAsync(CreateImageRequest createImageRequest)
```
    Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Elastic Container Registry (ECR). For more information, see Bring your own SageMaker image.
    
    Parameters:
    
    createImageRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateImage operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createImageAsync
```
Future<CreateImageResult> createImageAsync(CreateImageRequest createImageRequest,
                                           AsyncHandler<CreateImageRequest,CreateImageResult> asyncHandler)
```
    Creates a custom SageMaker image. A SageMaker image is a set of image versions. Each image version represents a container image stored in Amazon Elastic Container Registry (ECR). For more information, see Bring your own SageMaker image.
    
    Parameters:
    
    createImageRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateImage operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createImageVersionAsync
```
Future<CreateImageVersionResult> createImageVersionAsync(CreateImageVersionRequest createImageVersionRequest)
```
    Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Elastic Container Registry (ECR) container image specified by BaseImage.
    
    Parameters:
    
    createImageVersionRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateImageVersion operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createImageVersionAsync
```
Future<CreateImageVersionResult> createImageVersionAsync(CreateImageVersionRequest createImageVersionRequest,
                                                         AsyncHandler<CreateImageVersionRequest,CreateImageVersionResult> asyncHandler)
```
    Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Elastic Container Registry (ECR) container image specified by BaseImage.
    
    Parameters:
    
    createImageVersionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateImageVersion operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createInferenceRecommendationsJobAsync
```
Future<CreateInferenceRecommendationsJobResult> createInferenceRecommendationsJobAsync(CreateInferenceRecommendationsJobRequest createInferenceRecommendationsJobRequest)
```
    Starts a recommendation job. You can create either an instance recommendation or load test job.
    
    Parameters:
    
    createInferenceRecommendationsJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateInferenceRecommendationsJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createInferenceRecommendationsJobAsync
```
Future<CreateInferenceRecommendationsJobResult> createInferenceRecommendationsJobAsync(CreateInferenceRecommendationsJobRequest createInferenceRecommendationsJobRequest,
                                                                                       AsyncHandler<CreateInferenceRecommendationsJobRequest,CreateInferenceRecommendationsJobResult> asyncHandler)
```
    Starts a recommendation job. You can create either an instance recommendation or load test job.
    
    Parameters:
    
    createInferenceRecommendationsJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateInferenceRecommendationsJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createLabelingJobAsync
```
Future<CreateLabelingJobResult> createLabelingJobAsync(CreateLabelingJobRequest createLabelingJobRequest)
```
    Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models.
    
    You can select your workforce from one of three providers:
    - A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
    - One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
    - The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
    You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
    
    The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data.
    
    The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
    
    You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
    Parameters:
    
    createLabelingJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateLabelingJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createLabelingJobAsync
```
Future<CreateLabelingJobResult> createLabelingJobAsync(CreateLabelingJobRequest createLabelingJobRequest,
                                                       AsyncHandler<CreateLabelingJobRequest,CreateLabelingJobResult> asyncHandler)
```
    Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models.
    
    You can select your workforce from one of three providers:
    - A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.
    - One or more vendors that you select from the Amazon Web Services Marketplace. Vendors provide expertise in specific areas.
    - The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.
    You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling.
    
    The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data.
    
    The output can be used as the manifest file for another labeling job or as training data for your machine learning models.
    
    You can use this operation to create a static labeling job or a streaming labeling job. A static labeling job stops if all data objects in the input manifest file identified in ManifestS3Uri have been labeled. A streaming labeling job runs perpetually until it is manually stopped, or remains idle for 10 days. You can send new data objects to an active (InProgress) streaming labeling job in real time. To learn how to create a static labeling job, see Create a Labeling Job (API) in the Amazon SageMaker Developer Guide. To learn how to create a streaming labeling job, see Create a Streaming Labeling Job.
    Parameters:
    
    createLabelingJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateLabelingJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelAsync
```
Future<CreateModelResult> createModelAsync(CreateModelRequest createModelRequest)
```
    Creates a model in SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
    
    Use this API to create a model if you want to use SageMaker hosting services or run a batch transform job.
    
    To host your model, you create an endpoint configuration with the CreateEndpointConfig API, and then create an endpoint with the CreateEndpoint API. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
    
    For an example that calls this method when deploying a model to SageMaker hosting services, see Create a Model (Amazon Web Services SDK for Python (Boto 3)).
    
    To run a batch transform using your model, you start a job with the CreateTransformJob API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
    
    In the request, you also provide an IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
    
    Parameters:
    
    createModelRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateModel operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelAsync
```
Future<CreateModelResult> createModelAsync(CreateModelRequest createModelRequest,
                                           AsyncHandler<CreateModelRequest,CreateModelResult> asyncHandler)
```
    Creates a model in SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions.
    
    Use this API to create a model if you want to use SageMaker hosting services or run a batch transform job.
    
    To host your model, you create an endpoint configuration with the CreateEndpointConfig API, and then create an endpoint with the CreateEndpoint API. SageMaker then deploys all of the containers that you defined for the model in the hosting environment.
    
    For an example that calls this method when deploying a model to SageMaker hosting services, see Create a Model (Amazon Web Services SDK for Python (Boto 3)).
    
    To run a batch transform using your model, you start a job with the CreateTransformJob API. SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
    
    In the request, you also provide an IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other Amazon Web Services resources, you grant necessary permissions via this role.
    
    Parameters:
    
    createModelRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateModel operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelBiasJobDefinitionAsync
```
Future<CreateModelBiasJobDefinitionResult> createModelBiasJobDefinitionAsync(CreateModelBiasJobDefinitionRequest createModelBiasJobDefinitionRequest)
```
    Creates the definition for a model bias job.
    
    Parameters:
    
    createModelBiasJobDefinitionRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateModelBiasJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelBiasJobDefinitionAsync
```
Future<CreateModelBiasJobDefinitionResult> createModelBiasJobDefinitionAsync(CreateModelBiasJobDefinitionRequest createModelBiasJobDefinitionRequest,
                                                                             AsyncHandler<CreateModelBiasJobDefinitionRequest,CreateModelBiasJobDefinitionResult> asyncHandler)
```
    Creates the definition for a model bias job.
    
    Parameters:
    
    createModelBiasJobDefinitionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateModelBiasJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelExplainabilityJobDefinitionAsync
```
Future<CreateModelExplainabilityJobDefinitionResult> createModelExplainabilityJobDefinitionAsync(CreateModelExplainabilityJobDefinitionRequest createModelExplainabilityJobDefinitionRequest)
```
    Creates the definition for a model explainability job.
    
    Parameters:
    
    createModelExplainabilityJobDefinitionRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateModelExplainabilityJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelExplainabilityJobDefinitionAsync
```
Future<CreateModelExplainabilityJobDefinitionResult> createModelExplainabilityJobDefinitionAsync(CreateModelExplainabilityJobDefinitionRequest createModelExplainabilityJobDefinitionRequest,
                                                                                                 AsyncHandler<CreateModelExplainabilityJobDefinitionRequest,CreateModelExplainabilityJobDefinitionResult> asyncHandler)
```
    Creates the definition for a model explainability job.
    
    Parameters:
    
    createModelExplainabilityJobDefinitionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateModelExplainabilityJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelPackageAsync
```
Future<CreateModelPackageResult> createModelPackageAsync(CreateModelPackageRequest createModelPackageRequest)
```
    Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
    
    To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification.
    There are two types of model packages:
    
    Versioned - a model that is part of a model group in the model registry.
    
    Unversioned - a model package that is not part of a model group.
    Parameters:
    
    createModelPackageRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateModelPackage operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelPackageAsync
```
Future<CreateModelPackageResult> createModelPackageAsync(CreateModelPackageRequest createModelPackageRequest,
                                                         AsyncHandler<CreateModelPackageRequest,CreateModelPackageResult> asyncHandler)
```
    Creates a model package that you can use to create SageMaker models or list on Amazon Web Services Marketplace, or a versioned model that is part of a model group. Buyers can subscribe to model packages listed on Amazon Web Services Marketplace to create models in SageMaker.
    
    To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in Amazon Web Services Marketplace, provide a value for SourceAlgorithmSpecification.
    There are two types of model packages:
    
    Versioned - a model that is part of a model group in the model registry.
    
    Unversioned - a model package that is not part of a model group.
    Parameters:
    
    createModelPackageRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateModelPackage operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelPackageGroupAsync
```
Future<CreateModelPackageGroupResult> createModelPackageGroupAsync(CreateModelPackageGroupRequest createModelPackageGroupRequest)
```
    Creates a model group. A model group contains a group of model versions.
    
    Parameters:
    
    createModelPackageGroupRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateModelPackageGroup operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelPackageGroupAsync
```
Future<CreateModelPackageGroupResult> createModelPackageGroupAsync(CreateModelPackageGroupRequest createModelPackageGroupRequest,
                                                                   AsyncHandler<CreateModelPackageGroupRequest,CreateModelPackageGroupResult> asyncHandler)
```
    Creates a model group. A model group contains a group of model versions.
    
    Parameters:
    
    createModelPackageGroupRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateModelPackageGroup operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelQualityJobDefinitionAsync
```
Future<CreateModelQualityJobDefinitionResult> createModelQualityJobDefinitionAsync(CreateModelQualityJobDefinitionRequest createModelQualityJobDefinitionRequest)
```
    Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
    
    Parameters:
    
    createModelQualityJobDefinitionRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateModelQualityJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createModelQualityJobDefinitionAsync
```
Future<CreateModelQualityJobDefinitionResult> createModelQualityJobDefinitionAsync(CreateModelQualityJobDefinitionRequest createModelQualityJobDefinitionRequest,
                                                                                   AsyncHandler<CreateModelQualityJobDefinitionRequest,CreateModelQualityJobDefinitionResult> asyncHandler)
```
    Creates a definition for a job that monitors model quality and drift. For information about model monitor, see Amazon SageMaker Model Monitor.
    
    Parameters:
    
    createModelQualityJobDefinitionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateModelQualityJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createMonitoringScheduleAsync
```
Future<CreateMonitoringScheduleResult> createMonitoringScheduleAsync(CreateMonitoringScheduleRequest createMonitoringScheduleRequest)
```
    Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.
    
    Parameters:
    
    createMonitoringScheduleRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateMonitoringSchedule operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createMonitoringScheduleAsync
```
Future<CreateMonitoringScheduleResult> createMonitoringScheduleAsync(CreateMonitoringScheduleRequest createMonitoringScheduleRequest,
                                                                     AsyncHandler<CreateMonitoringScheduleRequest,CreateMonitoringScheduleResult> asyncHandler)
```
    Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.
    
    Parameters:
    
    createMonitoringScheduleRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateMonitoringSchedule operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createNotebookInstanceAsync
```
Future<CreateNotebookInstanceResult> createNotebookInstanceAsync(CreateNotebookInstanceRequest createNotebookInstanceRequest)
```
    Creates an SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
    
    In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
    
    SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.
    
    After receiving the request, SageMaker does the following:
    1. Creates a network interface in the SageMaker VPC.
    2. (Option) If you specified SubnetId, SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.
    3. Launches an EC2 instance of the type specified in the request in the SageMaker VPC. If you specified SubnetId of your VPC, SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
    After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.
    
    After SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker endpoints, and validate hosted models.
    
    For more information, see How It Works.
    Parameters:
    
    createNotebookInstanceRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateNotebookInstance operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createNotebookInstanceAsync
```
Future<CreateNotebookInstanceResult> createNotebookInstanceAsync(CreateNotebookInstanceRequest createNotebookInstanceRequest,
                                                                 AsyncHandler<CreateNotebookInstanceRequest,CreateNotebookInstanceResult> asyncHandler)
```
    Creates an SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
    
    In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.
    
    SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.
    
    After receiving the request, SageMaker does the following:
    1. Creates a network interface in the SageMaker VPC.
    2. (Option) If you specified SubnetId, SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.
    3. Launches an EC2 instance of the type specified in the request in the SageMaker VPC. If you specified SubnetId of your VPC, SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.
    After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.
    
    After SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker endpoints, and validate hosted models.
    
    For more information, see How It Works.
    Parameters:
    
    createNotebookInstanceRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateNotebookInstance operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createNotebookInstanceLifecycleConfigAsync
```
Future<CreateNotebookInstanceLifecycleConfigResult> createNotebookInstanceLifecycleConfigAsync(CreateNotebookInstanceLifecycleConfigRequest createNotebookInstanceLifecycleConfigRequest)
```
    Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance.
    
    Each lifecycle configuration script has a limit of 16384 characters.
    
    The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
    
    View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
    
    Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
    
    For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
    
    Parameters:
    
    createNotebookInstanceLifecycleConfigRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateNotebookInstanceLifecycleConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createNotebookInstanceLifecycleConfigAsync
```
Future<CreateNotebookInstanceLifecycleConfigResult> createNotebookInstanceLifecycleConfigAsync(CreateNotebookInstanceLifecycleConfigRequest createNotebookInstanceLifecycleConfigRequest,
                                                                                               AsyncHandler<CreateNotebookInstanceLifecycleConfigRequest,CreateNotebookInstanceLifecycleConfigResult> asyncHandler)
```
    Creates a lifecycle configuration that you can associate with a notebook instance. A lifecycle configuration is a collection of shell scripts that run when you create or start a notebook instance.
    
    Each lifecycle configuration script has a limit of 16384 characters.
    
    The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin.
    
    View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook].
    
    Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started.
    
    For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.
    
    Parameters:
    
    createNotebookInstanceLifecycleConfigRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateNotebookInstanceLifecycleConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createPipelineAsync
```
Future<CreatePipelineResult> createPipelineAsync(CreatePipelineRequest createPipelineRequest)
```
    Creates a pipeline using a JSON pipeline definition.
    
    Parameters:
    
    createPipelineRequest -
    
    Returns:
    
    A Java Future containing the result of the CreatePipeline operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createPipelineAsync
```
Future<CreatePipelineResult> createPipelineAsync(CreatePipelineRequest createPipelineRequest,
                                                 AsyncHandler<CreatePipelineRequest,CreatePipelineResult> asyncHandler)
```
    Creates a pipeline using a JSON pipeline definition.
    
    Parameters:
    
    createPipelineRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreatePipeline operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createPresignedDomainUrlAsync
```
Future<CreatePresignedDomainUrlResult> createPresignedDomainUrlAsync(CreatePresignedDomainUrlRequest createPresignedDomainUrlRequest)
```
    Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.
    
    The IAM role or user used to call this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.
    
    You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to SageMaker Studio Through an Interface VPC Endpoint .
    
    The URL that you get from a call to CreatePresignedDomainUrl has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
    
    Parameters:
    
    createPresignedDomainUrlRequest -
    
    Returns:
    
    A Java Future containing the result of the CreatePresignedDomainUrl operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createPresignedDomainUrlAsync
```
Future<CreatePresignedDomainUrlResult> createPresignedDomainUrlAsync(CreatePresignedDomainUrlRequest createPresignedDomainUrlRequest,
                                                                     AsyncHandler<CreatePresignedDomainUrlRequest,CreatePresignedDomainUrlResult> asyncHandler)
```
    Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM.
    
    The IAM role or user used to call this API defines the permissions to access the app. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the app.
    
    You can restrict access to this API and to the URL that it returns to a list of IP addresses, Amazon VPCs or Amazon VPC Endpoints that you specify. For more information, see Connect to SageMaker Studio Through an Interface VPC Endpoint .
    
    The URL that you get from a call to CreatePresignedDomainUrl has a default timeout of 5 minutes. You can configure this value using ExpiresInSeconds. If you try to use the URL after the timeout limit expires, you are directed to the Amazon Web Services console sign-in page.
    
    Parameters:
    
    createPresignedDomainUrlRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreatePresignedDomainUrl operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createPresignedNotebookInstanceUrlAsync
```
Future<CreatePresignedNotebookInstanceUrlResult> createPresignedNotebookInstanceUrlAsync(CreatePresignedNotebookInstanceUrlRequest createPresignedNotebookInstanceUrlRequest)
```
    Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker console, when you choose Open next to a notebook instance, SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
    
    The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
    
    You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
    
    The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
    
    Parameters:
    
    createPresignedNotebookInstanceUrlRequest -
    
    Returns:
    
    A Java Future containing the result of the CreatePresignedNotebookInstanceUrl operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createPresignedNotebookInstanceUrlAsync
```
Future<CreatePresignedNotebookInstanceUrlResult> createPresignedNotebookInstanceUrlAsync(CreatePresignedNotebookInstanceUrlRequest createPresignedNotebookInstanceUrlRequest,
                                                                                         AsyncHandler<CreatePresignedNotebookInstanceUrlRequest,CreatePresignedNotebookInstanceUrlResult> asyncHandler)
```
    Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the SageMaker console, when you choose Open next to a notebook instance, SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page.
    
    The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance.
    
    You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address.
    
    The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the Amazon Web Services console sign-in page.
    
    Parameters:
    
    createPresignedNotebookInstanceUrlRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreatePresignedNotebookInstanceUrl operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createProcessingJobAsync
```
Future<CreateProcessingJobResult> createProcessingJobAsync(CreateProcessingJobRequest createProcessingJobRequest)
```
    Creates a processing job.
    
    Parameters:
    
    createProcessingJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateProcessingJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createProcessingJobAsync
```
Future<CreateProcessingJobResult> createProcessingJobAsync(CreateProcessingJobRequest createProcessingJobRequest,
                                                           AsyncHandler<CreateProcessingJobRequest,CreateProcessingJobResult> asyncHandler)
```
    Creates a processing job.
    
    Parameters:
    
    createProcessingJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateProcessingJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createProjectAsync
```
Future<CreateProjectResult> createProjectAsync(CreateProjectRequest createProjectRequest)
```
    Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
    
    Parameters:
    
    createProjectRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateProject operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createProjectAsync
```
Future<CreateProjectResult> createProjectAsync(CreateProjectRequest createProjectRequest,
                                               AsyncHandler<CreateProjectRequest,CreateProjectResult> asyncHandler)
```
    Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.
    
    Parameters:
    
    createProjectRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateProject operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createStudioLifecycleConfigAsync
```
Future<CreateStudioLifecycleConfigResult> createStudioLifecycleConfigAsync(CreateStudioLifecycleConfigRequest createStudioLifecycleConfigRequest)
```
    Creates a new Studio Lifecycle Configuration.
    
    Parameters:
    
    createStudioLifecycleConfigRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateStudioLifecycleConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createStudioLifecycleConfigAsync
```
Future<CreateStudioLifecycleConfigResult> createStudioLifecycleConfigAsync(CreateStudioLifecycleConfigRequest createStudioLifecycleConfigRequest,
                                                                           AsyncHandler<CreateStudioLifecycleConfigRequest,CreateStudioLifecycleConfigResult> asyncHandler)
```
    Creates a new Studio Lifecycle Configuration.
    
    Parameters:
    
    createStudioLifecycleConfigRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateStudioLifecycleConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createTrainingJobAsync
```
Future<CreateTrainingJobResult> createTrainingJobAsync(CreateTrainingJobRequest createTrainingJobRequest)
```
    Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
    
    If you choose to host your model using SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than SageMaker, provided that you know how to use them for inference.
    
    In the request body, you provide the following:
    - AlgorithmSpecification - Identifies the training algorithm to use.
    - HyperParameters - Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
    - InputDataConfig - Describes the training dataset and the Amazon S3, EFS, or FSx location where it is stored.
    - OutputDataConfig - Identifies the Amazon S3 bucket where you want SageMaker to save the results of model training.
    - ResourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
    - EnableManagedSpotTraining - Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training.
    - RoleArn - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training.
    - StoppingCondition - To help cap training costs, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds to specify how long a managed spot training job has to complete.
    - Environment - The environment variables to set in the Docker container.
    - RetryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.
    For more information about SageMaker, see How It Works.
    Parameters:
    
    createTrainingJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateTrainingJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createTrainingJobAsync
```
Future<CreateTrainingJobResult> createTrainingJobAsync(CreateTrainingJobRequest createTrainingJobRequest,
                                                       AsyncHandler<CreateTrainingJobRequest,CreateTrainingJobResult> asyncHandler)
```
    Starts a model training job. After training completes, SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify.
    
    If you choose to host your model using SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than SageMaker, provided that you know how to use them for inference.
    
    In the request body, you provide the following:
    - AlgorithmSpecification - Identifies the training algorithm to use.
    - HyperParameters - Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this learning process. For a list of hyperparameters for each training algorithm provided by SageMaker, see Algorithms.
    - InputDataConfig - Describes the training dataset and the Amazon S3, EFS, or FSx location where it is stored.
    - OutputDataConfig - Identifies the Amazon S3 bucket where you want SageMaker to save the results of model training.
    - ResourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.
    - EnableManagedSpotTraining - Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training.
    - RoleArn - The Amazon Resource Name (ARN) that SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that SageMaker can successfully complete model training.
    - StoppingCondition - To help cap training costs, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds to specify how long a managed spot training job has to complete.
    - Environment - The environment variables to set in the Docker container.
    - RetryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.
    For more information about SageMaker, see How It Works.
    Parameters:
    
    createTrainingJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateTrainingJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createTransformJobAsync
```
Future<CreateTransformJobResult> createTransformJobAsync(CreateTransformJobRequest createTransformJobRequest)
```
    Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
    
    To perform batch transformations, you create a transform job and use the data that you have readily available.
    
    In the request body, you provide the following:
    - TransformJobName - Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
    - ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see CreateModel.
    - TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.
    - TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
    - TransformResources - Identifies the ML compute instances for the transform job.
    For more information about how batch transformation works, see Batch Transform.
    Parameters:
    
    createTransformJobRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateTransformJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createTransformJobAsync
```
Future<CreateTransformJobResult> createTransformJobAsync(CreateTransformJobRequest createTransformJobRequest,
                                                         AsyncHandler<CreateTransformJobRequest,CreateTransformJobResult> asyncHandler)
```
    Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.
    
    To perform batch transformations, you create a transform job and use the data that you have readily available.
    
    In the request body, you provide the following:
    - TransformJobName - Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.
    - ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see CreateModel.
    - TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.
    - TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
    - TransformResources - Identifies the ML compute instances for the transform job.
    For more information about how batch transformation works, see Batch Transform.
    Parameters:
    
    createTransformJobRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateTransformJob operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createTrialAsync
```
Future<CreateTrialResult> createTrialAsync(CreateTrialRequest createTrialRequest)
```
    Creates an SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single SageMaker experiment.
    
    When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
    
    You can add tags to a trial and then use the Search API to search for the tags.
    
    To get a list of all your trials, call the ListTrials API. To view a trial's properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
    
    Parameters:
    
    createTrialRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateTrial operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createTrialAsync
```
Future<CreateTrialResult> createTrialAsync(CreateTrialRequest createTrialRequest,
                                           AsyncHandler<CreateTrialRequest,CreateTrialResult> asyncHandler)
```
    Creates an SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single SageMaker experiment.
    
    When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
    
    You can add tags to a trial and then use the Search API to search for the tags.
    
    To get a list of all your trials, call the ListTrials API. To view a trial's properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.
    
    Parameters:
    
    createTrialRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateTrial operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createTrialComponentAsync
```
Future<CreateTrialComponentResult> createTrialComponentAsync(CreateTrialComponentRequest createTrialComponentRequest)
```
    Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials.
    
    Trial components include pre-processing jobs, training jobs, and batch transform jobs.
    
    When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
    
    You can add tags to a trial component and then use the Search API to search for the tags.
    
    Parameters:
    
    createTrialComponentRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateTrialComponent operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createTrialComponentAsync
```
Future<CreateTrialComponentResult> createTrialComponentAsync(CreateTrialComponentRequest createTrialComponentRequest,
                                                             AsyncHandler<CreateTrialComponentRequest,CreateTrialComponentResult> asyncHandler)
```
    Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials.
    
    Trial components include pre-processing jobs, training jobs, and batch transform jobs.
    
    When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
    
    You can add tags to a trial component and then use the Search API to search for the tags.
    
    Parameters:
    
    createTrialComponentRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateTrialComponent operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createUserProfileAsync
```
Future<CreateUserProfileResult> createUserProfileAsync(CreateUserProfileRequest createUserProfileRequest)
```
    Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.
    
    Parameters:
    
    createUserProfileRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateUserProfile operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createUserProfileAsync
```
Future<CreateUserProfileResult> createUserProfileAsync(CreateUserProfileRequest createUserProfileRequest,
                                                       AsyncHandler<CreateUserProfileRequest,CreateUserProfileResult> asyncHandler)
```
    Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.
    
    Parameters:
    
    createUserProfileRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateUserProfile operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createWorkforceAsync
```
Future<CreateWorkforceResult> createWorkforceAsync(CreateWorkforceRequest createWorkforceRequest)
```
    Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
    
    If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
    
    To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
    
    To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).
    
    Parameters:
    
    createWorkforceRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateWorkforce operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createWorkforceAsync
```
Future<CreateWorkforceResult> createWorkforceAsync(CreateWorkforceRequest createWorkforceRequest,
                                                   AsyncHandler<CreateWorkforceRequest,CreateWorkforceResult> asyncHandler)
```
    Use this operation to create a workforce. This operation will return an error if a workforce already exists in the Amazon Web Services Region that you specify. You can only create one workforce in each Amazon Web Services Region per Amazon Web Services account.
    
    If you want to create a new workforce in an Amazon Web Services Region where a workforce already exists, use the API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce.
    
    To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).
    
    To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP).
    
    Parameters:
    
    createWorkforceRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateWorkforce operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createWorkteamAsync
```
Future<CreateWorkteamResult> createWorkteamAsync(CreateWorkteamRequest createWorkteamRequest)
```
    Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.
    
    You cannot create more than 25 work teams in an account and region.
    
    Parameters:
    
    createWorkteamRequest -
    
    Returns:
    
    A Java Future containing the result of the CreateWorkteam operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - createWorkteamAsync
```
Future<CreateWorkteamResult> createWorkteamAsync(CreateWorkteamRequest createWorkteamRequest,
                                                 AsyncHandler<CreateWorkteamRequest,CreateWorkteamResult> asyncHandler)
```
    Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.
    
    You cannot create more than 25 work teams in an account and region.
    
    Parameters:
    
    createWorkteamRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the CreateWorkteam operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteActionAsync
```
Future<DeleteActionResult> deleteActionAsync(DeleteActionRequest deleteActionRequest)
```
    Deletes an action.
    
    Parameters:
    
    deleteActionRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteAction operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteActionAsync
```
Future<DeleteActionResult> deleteActionAsync(DeleteActionRequest deleteActionRequest,
                                             AsyncHandler<DeleteActionRequest,DeleteActionResult> asyncHandler)
```
    Deletes an action.
    
    Parameters:
    
    deleteActionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteAction operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteAlgorithmAsync
```
Future<DeleteAlgorithmResult> deleteAlgorithmAsync(DeleteAlgorithmRequest deleteAlgorithmRequest)
```
    Removes the specified algorithm from your account.
    
    Parameters:
    
    deleteAlgorithmRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteAlgorithm operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteAlgorithmAsync
```
Future<DeleteAlgorithmResult> deleteAlgorithmAsync(DeleteAlgorithmRequest deleteAlgorithmRequest,
                                                   AsyncHandler<DeleteAlgorithmRequest,DeleteAlgorithmResult> asyncHandler)
```
    Removes the specified algorithm from your account.
    
    Parameters:
    
    deleteAlgorithmRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteAlgorithm operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteAppAsync
```
Future<DeleteAppResult> deleteAppAsync(DeleteAppRequest deleteAppRequest)
```
    Used to stop and delete an app.
    
    Parameters:
    
    deleteAppRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteApp operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteAppAsync
```
Future<DeleteAppResult> deleteAppAsync(DeleteAppRequest deleteAppRequest,
                                       AsyncHandler<DeleteAppRequest,DeleteAppResult> asyncHandler)
```
    Used to stop and delete an app.
    
    Parameters:
    
    deleteAppRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteApp operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteAppImageConfigAsync
```
Future<DeleteAppImageConfigResult> deleteAppImageConfigAsync(DeleteAppImageConfigRequest deleteAppImageConfigRequest)
```
    Deletes an AppImageConfig.
    
    Parameters:
    
    deleteAppImageConfigRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteAppImageConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteAppImageConfigAsync
```
Future<DeleteAppImageConfigResult> deleteAppImageConfigAsync(DeleteAppImageConfigRequest deleteAppImageConfigRequest,
                                                             AsyncHandler<DeleteAppImageConfigRequest,DeleteAppImageConfigResult> asyncHandler)
```
    Deletes an AppImageConfig.
    
    Parameters:
    
    deleteAppImageConfigRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteAppImageConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteArtifactAsync
```
Future<DeleteArtifactResult> deleteArtifactAsync(DeleteArtifactRequest deleteArtifactRequest)
```
    Deletes an artifact. Either ArtifactArn or Source must be specified.
    
    Parameters:
    
    deleteArtifactRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteArtifact operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteArtifactAsync
```
Future<DeleteArtifactResult> deleteArtifactAsync(DeleteArtifactRequest deleteArtifactRequest,
                                                 AsyncHandler<DeleteArtifactRequest,DeleteArtifactResult> asyncHandler)
```
    Deletes an artifact. Either ArtifactArn or Source must be specified.
    
    Parameters:
    
    deleteArtifactRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteArtifact operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteAssociationAsync
```
Future<DeleteAssociationResult> deleteAssociationAsync(DeleteAssociationRequest deleteAssociationRequest)
```
    Deletes an association.
    
    Parameters:
    
    deleteAssociationRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteAssociation operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteAssociationAsync
```
Future<DeleteAssociationResult> deleteAssociationAsync(DeleteAssociationRequest deleteAssociationRequest,
                                                       AsyncHandler<DeleteAssociationRequest,DeleteAssociationResult> asyncHandler)
```
    Deletes an association.
    
    Parameters:
    
    deleteAssociationRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteAssociation operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteCodeRepositoryAsync
```
Future<DeleteCodeRepositoryResult> deleteCodeRepositoryAsync(DeleteCodeRepositoryRequest deleteCodeRepositoryRequest)
```
    Deletes the specified Git repository from your account.
    
    Parameters:
    
    deleteCodeRepositoryRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteCodeRepository operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteCodeRepositoryAsync
```
Future<DeleteCodeRepositoryResult> deleteCodeRepositoryAsync(DeleteCodeRepositoryRequest deleteCodeRepositoryRequest,
                                                             AsyncHandler<DeleteCodeRepositoryRequest,DeleteCodeRepositoryResult> asyncHandler)
```
    Deletes the specified Git repository from your account.
    
    Parameters:
    
    deleteCodeRepositoryRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteCodeRepository operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteContextAsync
```
Future<DeleteContextResult> deleteContextAsync(DeleteContextRequest deleteContextRequest)
```
    Deletes an context.
    
    Parameters:
    
    deleteContextRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteContext operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteContextAsync
```
Future<DeleteContextResult> deleteContextAsync(DeleteContextRequest deleteContextRequest,
                                               AsyncHandler<DeleteContextRequest,DeleteContextResult> asyncHandler)
```
    Deletes an context.
    
    Parameters:
    
    deleteContextRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteContext operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteDataQualityJobDefinitionAsync
```
Future<DeleteDataQualityJobDefinitionResult> deleteDataQualityJobDefinitionAsync(DeleteDataQualityJobDefinitionRequest deleteDataQualityJobDefinitionRequest)
```
    Deletes a data quality monitoring job definition.
    
    Parameters:
    
    deleteDataQualityJobDefinitionRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteDataQualityJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteDataQualityJobDefinitionAsync
```
Future<DeleteDataQualityJobDefinitionResult> deleteDataQualityJobDefinitionAsync(DeleteDataQualityJobDefinitionRequest deleteDataQualityJobDefinitionRequest,
                                                                                 AsyncHandler<DeleteDataQualityJobDefinitionRequest,DeleteDataQualityJobDefinitionResult> asyncHandler)
```
    Deletes a data quality monitoring job definition.
    
    Parameters:
    
    deleteDataQualityJobDefinitionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteDataQualityJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteDeviceFleetAsync
```
Future<DeleteDeviceFleetResult> deleteDeviceFleetAsync(DeleteDeviceFleetRequest deleteDeviceFleetRequest)
```
    Deletes a fleet.
    
    Parameters:
    
    deleteDeviceFleetRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteDeviceFleet operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteDeviceFleetAsync
```
Future<DeleteDeviceFleetResult> deleteDeviceFleetAsync(DeleteDeviceFleetRequest deleteDeviceFleetRequest,
                                                       AsyncHandler<DeleteDeviceFleetRequest,DeleteDeviceFleetResult> asyncHandler)
```
    Deletes a fleet.
    
    Parameters:
    
    deleteDeviceFleetRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteDeviceFleet operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteDomainAsync
```
Future<DeleteDomainResult> deleteDomainAsync(DeleteDomainRequest deleteDomainRequest)
```
    Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using SSO. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
    
    Parameters:
    
    deleteDomainRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteDomain operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteDomainAsync
```
Future<DeleteDomainResult> deleteDomainAsync(DeleteDomainRequest deleteDomainRequest,
                                             AsyncHandler<DeleteDomainRequest,DeleteDomainResult> asyncHandler)
```
    Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using SSO. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.
    
    Parameters:
    
    deleteDomainRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteDomain operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteEndpointAsync
```
Future<DeleteEndpointResult> deleteEndpointAsync(DeleteEndpointRequest deleteEndpointRequest)
```
    Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
    
    SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't need to use the RevokeGrant API call.
    
    When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn , otherwise SageMaker cannot delete these resources.
    
    Parameters:
    
    deleteEndpointRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteEndpoint operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteEndpointAsync
```
Future<DeleteEndpointResult> deleteEndpointAsync(DeleteEndpointRequest deleteEndpointRequest,
                                                 AsyncHandler<DeleteEndpointRequest,DeleteEndpointResult> asyncHandler)
```
    Deletes an endpoint. SageMaker frees up all of the resources that were deployed when the endpoint was created.
    
    SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't need to use the RevokeGrant API call.
    
    When you delete your endpoint, SageMaker asynchronously deletes associated endpoint resources such as KMS key grants. You might still see these resources in your account for a few minutes after deleting your endpoint. Do not delete or revoke the permissions for your ExecutionRoleArn , otherwise SageMaker cannot delete these resources.
    
    Parameters:
    
    deleteEndpointRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteEndpoint operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteEndpointConfigAsync
```
Future<DeleteEndpointConfigResult> deleteEndpointConfigAsync(DeleteEndpointConfigRequest deleteEndpointConfigRequest)
```
    Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.
    
    You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
    
    Parameters:
    
    deleteEndpointConfigRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteEndpointConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteEndpointConfigAsync
```
Future<DeleteEndpointConfigResult> deleteEndpointConfigAsync(DeleteEndpointConfigRequest deleteEndpointConfigRequest,
                                                             AsyncHandler<DeleteEndpointConfigRequest,DeleteEndpointConfigResult> asyncHandler)
```
    Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration.
    
    You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.
    
    Parameters:
    
    deleteEndpointConfigRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteEndpointConfig operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteExperimentAsync
```
Future<DeleteExperimentResult> deleteExperimentAsync(DeleteExperimentRequest deleteExperimentRequest)
```
    Deletes an SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
    
    Parameters:
    
    deleteExperimentRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteExperiment operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteExperimentAsync
```
Future<DeleteExperimentResult> deleteExperimentAsync(DeleteExperimentRequest deleteExperimentRequest,
                                                     AsyncHandler<DeleteExperimentRequest,DeleteExperimentResult> asyncHandler)
```
    Deletes an SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.
    
    Parameters:
    
    deleteExperimentRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteExperiment operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteFeatureGroupAsync
```
Future<DeleteFeatureGroupResult> deleteFeatureGroupAsync(DeleteFeatureGroupRequest deleteFeatureGroupRequest)
```
    Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup. Data cannot be accessed from the OnlineStore immediately after DeleteFeatureGroup is called.
    
    Data written into the OfflineStore will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your OfflineStore are not deleted.
    
    Parameters:
    
    deleteFeatureGroupRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteFeatureGroup operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteFeatureGroupAsync
```
Future<DeleteFeatureGroupResult> deleteFeatureGroupAsync(DeleteFeatureGroupRequest deleteFeatureGroupRequest,
                                                         AsyncHandler<DeleteFeatureGroupRequest,DeleteFeatureGroupResult> asyncHandler)
```
    Delete the FeatureGroup and any data that was written to the OnlineStore of the FeatureGroup. Data cannot be accessed from the OnlineStore immediately after DeleteFeatureGroup is called.
    
    Data written into the OfflineStore will not be deleted. The Amazon Web Services Glue database and tables that are automatically created for your OfflineStore are not deleted.
    
    Parameters:
    
    deleteFeatureGroupRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteFeatureGroup operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteFlowDefinitionAsync
```
Future<DeleteFlowDefinitionResult> deleteFlowDefinitionAsync(DeleteFlowDefinitionRequest deleteFlowDefinitionRequest)
```
    Deletes the specified flow definition.
    
    Parameters:
    
    deleteFlowDefinitionRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteFlowDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteFlowDefinitionAsync
```
Future<DeleteFlowDefinitionResult> deleteFlowDefinitionAsync(DeleteFlowDefinitionRequest deleteFlowDefinitionRequest,
                                                             AsyncHandler<DeleteFlowDefinitionRequest,DeleteFlowDefinitionResult> asyncHandler)
```
    Deletes the specified flow definition.
    
    Parameters:
    
    deleteFlowDefinitionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteFlowDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteHumanTaskUiAsync
```
Future<DeleteHumanTaskUiResult> deleteHumanTaskUiAsync(DeleteHumanTaskUiRequest deleteHumanTaskUiRequest)
```
    Use this operation to delete a human task user interface (worker task template).
    
    To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
    
    Parameters:
    
    deleteHumanTaskUiRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteHumanTaskUi operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteHumanTaskUiAsync
```
Future<DeleteHumanTaskUiResult> deleteHumanTaskUiAsync(DeleteHumanTaskUiRequest deleteHumanTaskUiRequest,
                                                       AsyncHandler<DeleteHumanTaskUiRequest,DeleteHumanTaskUiResult> asyncHandler)
```
    Use this operation to delete a human task user interface (worker task template).
    
    To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.
    
    Parameters:
    
    deleteHumanTaskUiRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteHumanTaskUi operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteImageAsync
```
Future<DeleteImageResult> deleteImageAsync(DeleteImageRequest deleteImageRequest)
```
    Deletes a SageMaker image and all versions of the image. The container images aren't deleted.
    
    Parameters:
    
    deleteImageRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteImage operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteImageAsync
```
Future<DeleteImageResult> deleteImageAsync(DeleteImageRequest deleteImageRequest,
                                           AsyncHandler<DeleteImageRequest,DeleteImageResult> asyncHandler)
```
    Deletes a SageMaker image and all versions of the image. The container images aren't deleted.
    
    Parameters:
    
    deleteImageRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteImage operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteImageVersionAsync
```
Future<DeleteImageVersionResult> deleteImageVersionAsync(DeleteImageVersionRequest deleteImageVersionRequest)
```
    Deletes a version of a SageMaker image. The container image the version represents isn't deleted.
    
    Parameters:
    
    deleteImageVersionRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteImageVersion operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteImageVersionAsync
```
Future<DeleteImageVersionResult> deleteImageVersionAsync(DeleteImageVersionRequest deleteImageVersionRequest,
                                                         AsyncHandler<DeleteImageVersionRequest,DeleteImageVersionResult> asyncHandler)
```
    Deletes a version of a SageMaker image. The container image the version represents isn't deleted.
    
    Parameters:
    
    deleteImageVersionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteImageVersion operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteModelAsync
```
Future<DeleteModelResult> deleteModelAsync(DeleteModelRequest deleteModelRequest)
```
    Deletes a model. The DeleteModel API deletes only the model entry that was created in SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
    
    Parameters:
    
    deleteModelRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteModel operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteModelAsync
```
Future<DeleteModelResult> deleteModelAsync(DeleteModelRequest deleteModelRequest,
                                           AsyncHandler<DeleteModelRequest,DeleteModelResult> asyncHandler)
```
    Deletes a model. The DeleteModel API deletes only the model entry that was created in SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.
    
    Parameters:
    
    deleteModelRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteModel operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteModelBiasJobDefinitionAsync
```
Future<DeleteModelBiasJobDefinitionResult> deleteModelBiasJobDefinitionAsync(DeleteModelBiasJobDefinitionRequest deleteModelBiasJobDefinitionRequest)
```
    Deletes an Amazon SageMaker model bias job definition.
    
    Parameters:
    
    deleteModelBiasJobDefinitionRequest -
    
    Returns:
    
    A Java Future containing the result of the DeleteModelBiasJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteModelBiasJobDefinitionAsync
```
Future<DeleteModelBiasJobDefinitionResult> deleteModelBiasJobDefinitionAsync(DeleteModelBiasJobDefinitionRequest deleteModelBiasJobDefinitionRequest,
                                                                             AsyncHandler<DeleteModelBiasJobDefinitionRequest,DeleteModelBiasJobDefinitionResult> asyncHandler)
```
    Deletes an Amazon SageMaker model bias job definition.
    
    Parameters:
    
    deleteModelBiasJobDefinitionRequest -
    
    asyncHandler - Asynchronous callback handler for events in the lifecycle of the request. Users can provide an implementation of the callback methods in this interface to receive notification of successful or unsuccessful completion of the operation.
    
    Returns:
    
    A Java Future containing the result of the DeleteModelBiasJobDefinition operation returned by the service.
    
    See Also:
    
    AWS API Documentation
  - deleteModelExplainabilityJobDefinitionAsync
```
Future<
```

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Interface AmazonSageMakerAsync

Field Summary

Fields inherited from interface com.amazonaws.services.sagemaker.AmazonSageMaker

Method Summary

Methods inherited from interface com.amazonaws.services.sagemaker.AmazonSageMaker

Method Detail

addAssociationAsync

addAssociationAsync

addTagsAsync

addTagsAsync

associateTrialComponentAsync

associateTrialComponentAsync

batchDescribeModelPackageAsync

batchDescribeModelPackageAsync

createActionAsync

createActionAsync

createAlgorithmAsync

createAlgorithmAsync

createAppAsync

createAppAsync

createAppImageConfigAsync

createAppImageConfigAsync

createArtifactAsync

createArtifactAsync

createAutoMLJobAsync

createAutoMLJobAsync

createCodeRepositoryAsync

createCodeRepositoryAsync

createCompilationJobAsync

createCompilationJobAsync

createContextAsync

createContextAsync

createDataQualityJobDefinitionAsync

createDataQualityJobDefinitionAsync

createDeviceFleetAsync

createDeviceFleetAsync

createDomainAsync

createDomainAsync

createEdgePackagingJobAsync

createEdgePackagingJobAsync

createEndpointAsync

createEndpointAsync

createEndpointConfigAsync

createEndpointConfigAsync

createExperimentAsync

createExperimentAsync

createFeatureGroupAsync

createFeatureGroupAsync

createFlowDefinitionAsync

createFlowDefinitionAsync

createHumanTaskUiAsync

createHumanTaskUiAsync

createHyperParameterTuningJobAsync

createHyperParameterTuningJobAsync

createImageAsync

createImageAsync

createImageVersionAsync

createImageVersionAsync

createInferenceRecommendationsJobAsync

createInferenceRecommendationsJobAsync

createLabelingJobAsync

createLabelingJobAsync

createModelAsync

createModelAsync

createModelBiasJobDefinitionAsync

createModelBiasJobDefinitionAsync

createModelExplainabilityJobDefinitionAsync

createModelExplainabilityJobDefinitionAsync

createModelPackageAsync

createModelPackageAsync

createModelPackageGroupAsync

createModelPackageGroupAsync

createModelQualityJobDefinitionAsync

createModelQualityJobDefinitionAsync

createMonitoringScheduleAsync

createMonitoringScheduleAsync

createNotebookInstanceAsync

createNotebookInstanceAsync

createNotebookInstanceLifecycleConfigAsync