AWS Developers | Prepare ML data faster and at scale with Amazon SageMaker - AWS Machine Learning in 15 @awsdevelopers | Uploaded 1 year ago | Updated 1 hour ago
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Data preparation for ML is a difficult process. It requires extracting and normalizing data and performing feature engineering, which can be time consuming. With Amazon SageMaker you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, bias detection, and visualization from a single visual interface. In this video, you'll learn how you can use Amazon SageMaker to reduce the time it takes to aggregate and prepare structured data for ML from weeks to minutes.

📥💼 Download slides: pages.awscloud.com/rs/112-TZM-766/images/2023_VW-0917-MCL_Slide-Deck.pdf

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