Front matter
forewords
preface
acknowledgments
about this book
about the author
about the cover illustration
1 Introduction to Bayesian optimization
1.1 Finding the optimum of an expensive black box function
Hyperparameter tuning as an example of an expensive black box optimization problem
The problem of expensive black box optimization
Other real-world examples of expensive black box optimization problems
1.2 Introducing Bayesian optimization
Modeling with a Gaussian process
Making decisions with a BayesOpt policy
Combining the GP and the optimization policy to form the optimization loop
BayesOpt in action
1.3 What will you learn in this book?
(try again in a couple of minutes)