Machine learning offers the potential to train data-based models and therefore to extract knowledge from data. One key design decision is the selection of hyperparameters of a machine learning algorithm. Hyperparameter optimization techniques automatically tune the hyperparameters – but choosing the best technique depends highly on the use case. This book presents a decision support system for the selection of hyperparameter optimization techniques in the production domain.