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An oscilloscope for deep learning

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Manage episode 300275900 series 2570898
Content provided by Ben Lorica. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Lorica 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://player.fm/legal.

This week’s guest is Charles Martin, independent researcher and founder of Calculation Consulting, a boutique consultancy focused on data science and machine learning. Along with Michael Mahoney and Serena Peng, Charles is co-author of a recent Nature paper on new methods for evaluating and tuning deep learning models (“Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data”).
Subscribe: AppleAndroidSpotifyStitcherGoogleRSS.
Detailed show notes can be found on The Data Exchange web site.
Subscribe to The Gradient Flow Newsletter.

  continue reading

241 episodes

Artwork
iconShare
 
Manage episode 300275900 series 2570898
Content provided by Ben Lorica. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ben Lorica 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://player.fm/legal.

This week’s guest is Charles Martin, independent researcher and founder of Calculation Consulting, a boutique consultancy focused on data science and machine learning. Along with Michael Mahoney and Serena Peng, Charles is co-author of a recent Nature paper on new methods for evaluating and tuning deep learning models (“Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data”).
Subscribe: AppleAndroidSpotifyStitcherGoogleRSS.
Detailed show notes can be found on The Data Exchange web site.
Subscribe to The Gradient Flow Newsletter.

  continue reading

241 episodes

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