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Evaluating models without test data (Practical AI #194)

Podcast |: Changelog Master Feed
Publisher |: Changelog Media
Media Type |: audio
Podknife tags |: Business,; Entrepreneurship,; Interview,; Master Feeds,; Software How-To,; Tech News,; Technology,; Web Development
Categories Via RSS |: Technology
Publication Date |: Sep 20, 2022
Episode Duration |: 00:44:55

Description
Content Encoded

WeightWatcher, created by Charles Martin, is an open source diagnostic tool for analyzing Neural Networks without training or even test data! Charles joins us in this episode to discuss the tool and how it fills certain gaps in current model evaluation workflows. Along the way, we discuss statistical methods from physics and a variety of practical ways to modify your training runs.

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Featuring:

Charles Martin – Twitter, GitHub, LinkedIn
Chris Benson – Twitter, GitHub, LinkedIn, Website
Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

Something missing or broken? ai-194.md">PRs welcome!

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