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Bayesian Optimization for Hyperparameter Tuning with Scott Clark - TWiML Talk #50
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Sam Charrington

· 47 Minutes

PodcastThe TWIML AI Podcast

Bayesian Optimization for Hyperparameter Tuning with Scott Clark - TWiML Talk #50

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As you all know, a few weeks ago, I spent some time in SF at the Artificial Intelligence Conference. While I was there, I had just enough time to sneak away and catch up with Scott Clark, Co-Founder and CEO of Sigopt, a company whose software is focused on automatically tuning your model’s parameters through Bayesian optimization. We dive pretty deeply into that process through the course of this discussion, while hitting on topics like Exploration vs Exploitation, Bayesian Regression, Heterogeneous Configuration Models and Covariance Kernels. I had a great time and learned a ton, but be forewarned, this is most definitely a Nerd Alert show! Notes for this show can be found at twimlai.com/talk/50

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This story was published by The TWIML AI Podcast and written by Sam Charrington. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on chtbl.com

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