A curated list of Gradient Boosting resources for Data Scientists
List of content
- Wikipedia - Gradient Boosting
- XGBoost - Introduction to Boosted Trees
- Kaggle - a kaggle master explains gradient boosting
- XGBoost
- XGBoost Github
- XGBoost Documentation
- XGBoost Paper - XGBoost: A Scalable Tree Boosting System
- LightGBM
- LightGBM Github
- LightGBM Documentation
- LightGBM Paper - LightGBM: A Highly Efficient Gradient Boosting Decision Tree
- Catboost
- Catboost Github
- Catboost Documentation
- Catboost Paper - CatBoost: unbiased boosting with categorical features
- Other
- Hyperspace - Hyperparameters Spaces for Optimization
- XGBoost - Complete Guide to Parameter Tuning in XGBoost (with codes in Python)
- LightGBM - parameters tuning guides for different scenarios
- Catboost - some tips on the possible parameter settings
- Gradient Boosting Explained - by Brilliantly wrong thoughts on science and programming
- Gradient Boosting From Scratch - by ML Review
- CatBoost vs. Light GBM vs. XGBoost - by Alvira Swalin on Towards Data Science
- Mastering The New Generation of Gradient Boosting - by Tal Peretz on Towards Data Science
- Catboost - Anna Veronika Dorogush on pydata
- Can one do better than XGBoost? - Mateusz Susik on pydata
- Kaggle XGBoost
- Catboost + LightGBM + XGBoost - comparison of the 3 implementations on categorical dataset.
To the extent possible under law, Tal Peretz has waived all copyright and related or neighboring rights to this work.