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#####################
XGBoost Documentation
#####################
**XGBoost** is an optimized distributed gradient boosting library designed to be highly **efficient**, **flexible** and **portable**.
It implements machine learning algorithms under the `Gradient Boosting <https://en.wikipedia.org/wiki/Gradient_boosting>`_ framework.
XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way.
The same code runs on major distributed environment (Hadoop, SGE, MPI) and can solve problems beyond billions of examples.
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Contents
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.. toctree::
:maxdepth: 2
:titlesonly:
install
build
get_started
tutorials/index
faq
GPU Support <gpu/index>
parameter
prediction
treemethod
Python Package <python/index>
R Package <R-package/index>
JVM Package <jvm/index>
Ruby Package <https://github.com/ankane/xgboost-ruby>
Swift Package <https://github.com/kongzii/SwiftXGBoost>
Julia Package <julia>
C Package <c>
C++ Interface <c++>
CLI Interface <cli>
contrib/index
changes/index
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