Amazon SageMaker Studio Lab - Amazon SageMaker
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Amazon SageMaker Studio Lab

Amazon SageMaker Studio Lab is a free service that gives customers access to Amazon compute resources, in an environment based on open-source JupyterLab. It is based on the same architecture and user interface as Amazon SageMaker Studio Classic, but with a subset of Studio Classic capabilities.

With Studio Lab, you can use Amazon compute resources to create and run your Jupyter notebooks without signing up for an Amazon account. Because Studio Lab is based on open-source JupyterLab, you can take advantage of open-source Jupyter extensions to run your Jupyter notebooks.

Studio Lab compared to Amazon SageMaker Studio Classic

While Studio Lab provides free access to Amazon compute resources, Amazon SageMaker Studio Classic provides the following advanced machine learning capabilities that Studio Lab does not support.

  • Continuous integration and continuous delivery (SageMaker Pipelines)

  • Real-time predictions

  • Large-scale distributed training

  • Data preparation (Amazon SageMaker Data Wrangler)

  • Data labeling (Amazon SageMaker Ground Truth)

  • Feature Store

  • Bias analysis (Clarify)

  • Model deployment

  • Model monitoring

Studio Classic also supports fine-grained access control and security by using Amazon Identity and Access Management (IAM), Amazon Virtual Private Cloud (Amazon VPC), and Amazon Key Management Service (Amazon KMS). Studio Lab does not support these Studio Classic features, nor does it support the use of estimators and built-in SageMaker algorithms.

To export your Studio Lab projects for use with Studio Classic, see Export an Amazon SageMaker Studio Lab environment to Amazon SageMaker Studio Classic.

The following topics give information about Studio Lab and how to use it

Topics