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Evaluating models without test data
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Daniel Whitenack and Chris Benson

· 45 Minutes

PodcastPractical AI

Evaluating models without test data

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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.

Featuring:

  • Charles Martin – GitHub, LinkedIn, X
  • Chris Benson – Website, GitHub, LinkedIn, X
  • Daniel Whitenack – Website, GitHub, X

Show Notes:

  • WeightWatcher
  • Talk from the Silicon Valley ACM meetup
  • A deep dive into the theory behind WeightWatcher (a talk from ENS)

Upcoming Events: 

  • Register for upcoming webinars here!

Original source

This story was published by Practical AI and written by Daniel Whitenack and Chris Benson. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on share.transistor.fm

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