Amazon re:MARS 2022 - Exploratory data analysis and automated feature engineering (MLR311)

Exploratory data analysis (EDA) is a critical step in the machine learning (ML) journey. Data scientists must explore their datasets to understand them, clean them, and perform feature engineering. In this session, consider how EDA is rapidly changing with the introduction and evolution of tools that prepare data for ML without requiring users to write code. Dive deep into two features of Amazon SageMaker Data Wrangler: automated insights into data quality and feature engineering and the ability to generate hundreds of features on time-series data with a single click.


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[akashsethi]

What a clear and awesome presentation. Thank you for explaining things so nicely!