Evaluating models without test data

Evaluating models without test data

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Episode
196 of 343
Duration
44min
Language
English
Format
Category
Non-fiction

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 • , X • Daniel Whitenack – Website • , GitHub • , X Show Notes:

WeightWatcherTalk from the Silicon Valley ACM meetupA deep dive into the theory behind WeightWatcher (a talk from ENS) Something missing or broken? PRs welcome!


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