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BITESIZE | Is Bayesian Optimization the Answer?
Manage episode 502796531 series 2969169
Today’s clip is from episode 139 of the podcast, with with Max Balandat.
Alex and Max discuss the integration of BoTorch with PyTorch, exploring its applications in Bayesian optimization and Gaussian processes. They highlight the advantages of using GPyTorch for structured matrices and the flexibility it offers for research.
The discussion also covers the motivations behind building BoTorch, the importance of open-source culture at Meta, and the role of PyTorch in modern machine learning.
Get the full discussion here.
Attend Alex's tutorial at PyData Berlin: A Beginner's Guide to State Space Modeling
- Intro to Bayes Course (first 2 lessons free)
- Advanced Regression Course (first 2 lessons free)
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!
Visit our Patreon page to unlock exclusive Bayesian swag ;)
Transcript
This is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.
167 Episoden
Manage episode 502796531 series 2969169
Today’s clip is from episode 139 of the podcast, with with Max Balandat.
Alex and Max discuss the integration of BoTorch with PyTorch, exploring its applications in Bayesian optimization and Gaussian processes. They highlight the advantages of using GPyTorch for structured matrices and the flexibility it offers for research.
The discussion also covers the motivations behind building BoTorch, the importance of open-source culture at Meta, and the role of PyTorch in modern machine learning.
Get the full discussion here.
Attend Alex's tutorial at PyData Berlin: A Beginner's Guide to State Space Modeling
- Intro to Bayes Course (first 2 lessons free)
- Advanced Regression Course (first 2 lessons free)
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!
Visit our Patreon page to unlock exclusive Bayesian swag ;)
Transcript
This is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.
167 Episoden
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