In this hands-on exercise, you are encouraged to use Auto Machine Learning libraries that automate the end-to-end process of applying machine learning to real-world problems. These libraries handle tasks such as data preprocessing, feature selection (!!), model selection, and hyperparameter tuning. This greatly simplifies the technical details, allowing us to focus more on physics. The goal of this challenge is to identify leptons (electrons and muons) from other particles using simulated data (MC) from the Belle II experiment.