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Train and deploy deep learning models using JAX with Amazon SageMaker


Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale. Typically, you can use the pre-built and optimized training and inference containers that have been optimized for AWS hardware. Although those containers cover many deep learning workloads, you may have use cases where you want to use a different framework or otherwise customize the contents of your OS libraries within the container. To accommodate this, SageMaker provides the flexibility to train models using any framework that can run in a Docker container. This functionality enables you to use existing SageMaker training capabilities such as training jobs, hyperparameter tuning, and Managed Spot Training.
Although we primarily cover training jobs …

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