I am working on an outline for an introductory XGBoost book for Packt publishing. I’m looking for some insight into advanced topics with XGBoost to structure later chapters. Beyond hyperparameter tuning, what makes an XGBoost model advanced? What topics should be covered in an introductory book that may be skipped over?
Any insights or ideas are welcome.