<img src=http://storage.mds.yandex.net/get-devtools-opensource/250854/catboost-logo.png width=300/>

[Website](https://catboost.yandex) |
[Documentation](https://tech.yandex.com/catboost/doc/dg/concepts/about-docpage/) |
[Installation](https://tech.yandex.com/catboost/doc/dg/concepts/cli-installation-docpage/)

[![Build Status](https://travis-ci.org/catboost/catboost.svg?branch=master)](https://travis-ci.org/catboost/catboost)
[![Build Status](https://ci.appveyor.com/api/projects/status/github/catboost/catboost?branch=master&svg=true)](https://ci.appveyor.com/project/sab/catboost)
[![PyPI version](https://badge.fury.io/py/catboost.svg)](https://badge.fury.io/py/catboost)

CatBoost is a machine learning method based on gradient boosting over decision trees.

Main advantages of CatBoost:
  - Superior quality when compared with other GBDT libraries.
  - Best in class inference speed.
  - Support for both numerical and categorical features.
  - Fast GPU and multi-GPU (on one node) support for training.
  - Data visualization tools included.

The following implementations are available:
  - [Python package](https://tech.yandex.com/catboost/doc/dg/concepts/python-installation-docpage/)
  - [R package](https://tech.yandex.com/catboost/doc/dg/concepts/r-installation-docpage/)
  - [Command-line interface](https://tech.yandex.com/catboost/doc/dg/concepts/cli-installation-docpage/)


Tutorials
--------------
* Tutorials are avaliable [here](https://github.com/catboost/catboost/tree/master/catboost/tutorials).

Catboost models in production
--------------
* If you want to evaluate Catboost model in your application read [model api documentation](https://github.com/catboost/catboost/tree/master/catboost/CatboostModelAPI.md).

For contributors
--------------
* To contribute to CatBoost you need to first read CLA text and add to your pull request, that you agree to the terms of the CLA. More information can be found
in [CONTRIBUTING.md](https://github.com/catboost/catboost/blob/master/CONTRIBUTING.md)

* Instructions for contributors can be found [here](https://tech.yandex.com/catboost/doc/dg/concepts/development-and-contributions-docpage/).


News
--------------
* News are published on [twitter](https://twitter.com/catboostml).


Questions and bug reports
--------------
* For reporting bugs please use the [catboost/bugreport](https://github.com/catboost/catboost/issues) page.
* Ask your question about CatBoost on [Stack Overflow](https://stackoverflow.com/questions/tagged/catboost).


License
-------
© YANDEX LLC, 2017-2018. Licensed under the Apache License, Version 2.0. See LICENSE file for more details.