XGBoost, LightGBM & CatBoost — Roadmap Step & Resources
Production-grade gradient boosting libraries widely used in real-world ML
- Level: advanced
- Estimated time: 2 days
- Roadmap: Machine Learning
Before this step
Mini projects
- Train an XGBoost model on a tabular dataset and tune its key hyperparameters
Interview questions
- What makes XGBoost/LightGBM faster than a naive gradient boosting implementation?
Study resources
- XGBoost Documentation (Article) — The official XGBoost documentation, the most widely used gradient boosting library.
- XGBoost Part 1: Regression, Clearly Explained!!! (Video) — StatQuest's widely-loved explanation of how XGBoost actually works.
Part of
- Ensemble Methods — section
- Machine Learning roadmap — the full learning path