Bayesian optimization is an old technique revived by using machine learning models at its core. This enables a plethora of extensions that really make the technique a great match for several real world applications. We showcase several examples such as custom and chemical encodings, transfer learning and slot-based mixture modelling enabled by our open-source code BayBE (https://github.com/emdgroup/baybe). [more]