To date, ensemble models of trees are considered state-of-the-art for tasks on tabular datasets.

In this session, we will have an introduction to how ensemble models of trees improve performance and we will cover in detail the guidelines for Hyperparameter Tunning the best performing models for tabular datasets Random Forest, XGBoost, CATBoost and LightGBM including the differences between these models.