Amazon SageMaker Studio offers fully integrated development environments (IDEs) for machine learning (ML). In July 2023, we launched Amazon SageMaker Distribution, a collection of docker images which includes the most popular libraries for ML on Amazon SageMaker Studio and Amazon Studio Lab. Today, we are extending the support for Amazon SageMaker Distribution on two popular IDEs used by data scientists and ML developers - Code Editor, based on Visual Studio Code Open Source (Code-OSS), and JupyterLab available on Amazon SageMaker Studio.

SageMaker Distribution enables ML practitioners to get started quickly with their ML development on the IDEs of their choice. The IDEs comes preloaded with the latest version of SageMaker Distribution image. The pre-built image comes with most popular libraries including deep learning frameworks such as PyTorch, TensorFlow and Keras; popular python packages such as numpy, scikit-learn and pandas; and IDEs such as JupyterLab and Code Editor. The versions of these installed libraries and packages are compatible with each other. The SageMaker Distribution image can also be used to run SageMaker training jobs, so customers can now use the same runtime on Studio notebooks and SageMaker training enabling them to seamlessly transition from local experimentation to batch execution.

SageMaker Distribution is now available in all AWS regions in GPU variant and CPU variant. You can now get started with SageMaker-distribution by accessing it via ECR gallery or GitHub. To learn more, please refer to the blog post and SageMaker documentation.