Planning experiments is essential in scientific research. However, in recent years have seen the adoption of “adaptive experiment design” methods, which use data to repeatedly generate and verify hypotheses. Bayesian optimization is one such method that has gained much attention.
This book provides a detailed explanation of the theory and algorithm of Bayesian optimization, from the basics to application. It also introduces how to implement the algorithn using the Optuna black box optimization software.