Coding Bayesian Optimization (Bayes Opt) with BOTORCH - Python example for hyperparameter tuning
Bayesian Optimization is one of the most common optimization algorithms. While there are some black box packages for using it they don't allow a lot of custom changes and are not well suited for all problems. Facebook AI released a library called Botorch which enables the customization of all different layers of Bayes Opt (from GP-model up to the acquisition function). In this video, you get a top-level overview of how to code a Bayesian optimization from scratch and what to have in mind. Based on this knowledge you can then dive deeper into the single subparts to improve your own algorithm. It is a python based library!
Theory for BayesOpt: • Bayesian Optimization (Bayes Opt): Easy ex...
BOTORCH: https://botorch.org
Links for Chapters:
0:00 Intro
0:35 Show test function
2:26 Generate initial samples
7:05 One Bayes Opt iteration
17:56 Optimization Loop
28:55 Outro
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