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For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
Is there ever a “one-size fits all” approach for feature engineering? Find out this and more with Amanda Casari and Alice Zheng, co-authors of the Feature Engineering for Machine Learning book.
See more at databricks.com/data-brew
5
1919 ratings
For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
Is there ever a “one-size fits all” approach for feature engineering? Find out this and more with Amanda Casari and Alice Zheng, co-authors of the Feature Engineering for Machine Learning book.
See more at databricks.com/data-brew
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