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Evaluating models without test data (Practical AI #194)
Sep 20, 2022 · 44 min · 43.3 MB
0:00-44:55
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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.
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Featuring:
- Charles Martin – GitHub, LinkedIn, X
- Chris Benson – Website, GitHub, LinkedIn, Bluesky, 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)
Something missing or broken? PRs welcome!
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x.comWebsite
chrisbenson.comGitHub
github.comLinkedIn
linkedin.comBluesky
bsky.appX
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datadan.ioGitHub
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x.comWeightWatcher
github.comTalk from the Silicon Valley ACM meetup
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