SageMaker is an end-to-end ML framework. We'll review how SageMaker supports data scientists development lifecycle including, integration with Git source control, Notebook life-cycle, SageMaker Search for reviewing past experiments, tracking model lineage, hyper parameters optimization, etc. During the session we'll use the tools above, and integrate them with an end-to-end ML pipeline. Subscribe to AWS Online Tech Talks On AWS:
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