Quan Nguyen - Bayesian Optimization- Fundamentals, Implementation, and Practice | PyData Global 2022

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Video URL: https://www.youtube.com/watch?v=ImXOdgEgaTM

Contents

0:06 Talk Introduction 0:15 Presenter Introduction 0:34 Agenda: Bayesian Optimization 1:20 Black-box optimization: context and examples 6:13 Traditional/naive strategies for optimization may waste resources 9:42 Bayesian optimization: components and inner workings 11:39 A Gaussian process as the underpinning predictive model 15:41 The exploitation-exploration trade-off 18:03 An optimization policy for choosing the best course of action: Expected Improvement (EI) score 20:56 The Bayesian optimization loop in action from start to finish 21:44 Other Bayesian optimization policies 23:32 Successful use cases of Bayesian optimization 24:06 Implementing Bayesian optimization in Python: the Torch ecosystem 24:27 GPyTorch for Gaussian process modeling 25:13 BoTorch for Bayesian optimization policies 25:48 Bayesian optimization in the real world 27:19 Manning’s Bayesian Optimization in Action (a hands-on guide to Python implementation)