
Amazon SageMaker Studio now supports SageMaker Distribution, a pre-built Docker image containing 18 popular machine learning libraries that enables practitioners to quickly start ML development with compatible versions across frameworks like PyTorch and TensorFlow.


<div><p>This article announces support for SageMaker Distribution, a pre-built Docker image for machine learning, now available in Amazon SageMaker Studio.</p><ul><li>Pre-built Docker container with 18 popular ML libraries and frameworks</li><li>Includes PyTorch, TensorFlow, Keras, NumPy, scikit-learn, pandas, and Jupyter Lab</li><li>Compatible library versions eliminate dependency conflicts</li><li>Same runtime for Studio notebooks and SageMaker training jobs</li><li>Enables seamless transition from local experimentation to batch execution</li><li>Available in all AWS regions where SageMaker Studio is supported</li></ul><p>SageMaker Distribution accelerates ML development by providing a standardized, pre-configured environment with essential tools and libraries.</p></div>


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