
Sign up to save your podcasts
Or


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
By Databricks4.8
2020 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

386 Listeners

26,380 Listeners

9,724 Listeners

481 Listeners

626 Listeners

306 Listeners

233 Listeners

266 Listeners

2,592 Listeners

10,254 Listeners

1,573 Listeners

551 Listeners

678 Listeners

3,538 Listeners

34 Listeners