#####################
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.

********
Contents
********

.. toctree::
  :maxdepth: 2
  :titlesonly:

  install
  build
  get_started
  tutorials/index
  faq
  XGBoost User Forum <https://discuss.xgboost.ai>
  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/xgb>
  Swift Package <https://github.com/kongzii/SwiftXGBoost>
  Julia Package <julia>
  C Package <c>
  C++ Interface <c++>
  CLI Interface <cli>
  contrib/index