* [Learning to Rank — xgboost 2.0.2 documentation](https://xgboost.readthedocs.io/en/stable/tutorials/learning_to_rank.html)
* [XGBoost的原理、公式推导、Python实现和应用 - 知乎](https://zhuanlan.zhihu.com/p/162001079)
* [XGBoost JVM Package — xgboost 2.0.2 documentation](https://xgboost.readthedocs.io/en/stable/jvm/index.html)
* [Machine-Learning-with-Python/diabetes.csv at master · susanli2016/Machine-Learning-with-Python · GitHub](https://github.com/susanli2016/Machine-Learning-with-Python/blob/master/diabetes.csv)
* [Introduction to Boosted Trees — xgboost 2.0.2 documentation](https://xgboost.readthedocs.io/en/stable/tutorials/model.html)
* [medium.com](https://medium.com/m/global-identity-2?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Fa-beginners-guide-to-xgboost-87f5d4c30ed7)
* [1603.02754.pdf](https://arxiv.org/pdf/1603.02754.pdf)
* [About](https://xgboost.ai/about)
* [XGBoost](https://dmlc.cs.washington.edu/xgboost.html)
* [DART booster — xgboost 2.0.2 documentation](https://xgboost.readthedocs.io/en/stable/tutorials/dart.html)
* [A Gentle Introduction to XGBoost for Applied Machine Learning - MachineLearningMastery.com](https://machinelearningmastery.com/gentle-introduction-xgboost-applied-machine-learning/)
* [XGBoost – What Is It and Why Does It Matter?](https://www.nvidia.com/en-us/glossary/data-science/xgboost/)
* [xgboost 2.0.2 on PyPI - Libraries.io](https://libraries.io/pypi/xgboost)
* [Installation Guide — xgboost 1.2.1 documentation](https://xgboost.readthedocs.io/en/release_1.2.0/build.html)
* [xgboost · PyPI](https://pypi.org/project/xgboost/#files)
PS D:\Download> pip install .\xgboost-2.0.2-py3-none-win_amd64.whl
Processing d:\download\xgboost-2.0.2-py3-none-win_amd64.whl
Requirement already satisfied: numpy in c:\users\administrator\anaconda3\lib\site-packages (from xgboost==2.0.2) (1.24.3)
Requirement already satisfied: scipy in c:\users\administrator\anaconda3\lib\site-packages (from xgboost==2.0.2) (1.11.1)
Installing collected packages: xgboost
Successfully installed xgboost-2.0.2