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Preparing training data is a critical step in machine learning. Preparing data involves creating labelled data, creating features, visualizing the features, and processing the data so it can be made available for training. In this session, learn how to use SageMaker Data Wrangler to connect to the data sources, use prebuilt visualization templates and built-in data to transform and streamline the process of cleaning, verifying, and exploring data without having to write a single line of code. In this session, we provide a demonstration of how SageMaker Data Wrangler publishes the data to SageMaker Feature store and explain how to take data preparation workflows into production using SageMaker Pipelines.


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