This page provides a list of books dedicated to the topic of XGBoost in English.
XGBoost Books
Books are generally listed in the order they were published:
| Book Cover | Book Details |
|---|---|
 | XGBoost With Python: Gradient Boosted Trees with XGBoost and scikit-learn, Jason Brownlee, 2016. |
 | XGBoost: The Extreme Gradient Boosting for Mining Applications, Nonita Sharma, 2018. |
 | Hands-On Gradient Boosting with XGBoost and scikit-learn: Perform accessible machine learning and extreme gradient boosting with Python, Corey Wade, 2020. |
 | Time Series Forecasting with Python and XGBoost: An Ultimate Guide from a Data Scientist, How to Master Time Series with Supervised Machine Learning Methods, Dario Radečić, 2020. |
 | Effective XGBoost: Optimizing, Tuning, Understanding, and Deploying Classification Models, Matt Harrison, 2023. |
 | XGBoost: The Ultimate Guide to Extreme Gradient Boosting, Henri van Maarseveen, 2023. |
 | XGBoost for Regression Predictive Modeling and Time Series Analysis: Build Intuitive Understanding, Develop, Build, Evaluate And Deploy Model, Partha Pritam Deka and Joyce Weiner, 2024. |
Related Books
This section provdies books that are closely related, e.g. on the topic of gradient boosting or a related framework like lightgbm.
- Machine Learning With Boosting: A Beginner’s Guide, Scott Hartshorn, 2017.
- Practical Gradient Boosting: An deep dive into Gradient Boosting in Python, Guillaume Saupin, 2022.
- Gradient Boosting Machines: Propel your predictive power with Python, Hayden Van Der Post and Mike Smith, 2023.
- Machine Learning with LightGBM and Python: A practitioner’s guide to developing production-ready machine learning systems, Andrich Van Wyk, 2023.
- Gradient Boosting Unleashed: Unlocking the Potential of this Prolific ML Model, Henri van Maarseveen, 2023.
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