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Data Brew Season 2 Episode 4: Hyperparameter and Neural Architecture Search

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Manage episode 292448770 series 2814833
Content provided by Databricks. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Databricks or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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.
Liam Li is a leading researcher in the fields of hyperparameter optimization and neural architecture search, and is the author of the seminal Hyperband paper. In this session, Liam discusses the evolution of hyperparameter optimization techniques and illustrates how every data scientist can benefit from neural architecture search.
See more at databricks.com/data-brew

  continue reading

43 episodes

Artwork
iconShare
 
Manage episode 292448770 series 2814833
Content provided by Databricks. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Databricks or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

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.
Liam Li is a leading researcher in the fields of hyperparameter optimization and neural architecture search, and is the author of the seminal Hyperband paper. In this session, Liam discusses the evolution of hyperparameter optimization techniques and illustrates how every data scientist can benefit from neural architecture search.
See more at databricks.com/data-brew

  continue reading

43 episodes

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