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[![GitHub license](http://dmlc.github.io/img/apache2.svg)](./LICENSE)
[![CRAN Status Badge](http://www.r-pkg.org/badges/version/xgboost)](http://cran.r-project.org/web/packages/xgboost)
[![PyPI version](https://badge.fury.io/py/xgboost.svg)](https://pypi.python.org/pypi/xgboost/)
[![Gitter chat for developers at https://gitter.im/dmlc/xgboost](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/dmlc/xgboost?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
[Community](https://xgboost.ai/community) |
[Documentation](https://xgboost.readthedocs.org) |
[Resources](demo/README.md) |
[Contributors](CONTRIBUTORS.md) |
[Community](https://xgboost.ai/community) |
[Release Notes](NEWS.md)
XGBoost is an optimized distributed gradient boosting library designed to be highly ***efficient***, ***flexible*** and ***portable***.