Awesome CatBoost
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This page contains a moderated list of examples, tutorials, articles about CatBoost use cases. It is inspired by [awesome-machine-learning](https://github.com/dmlc/mxnet/blob/master/example/README.md).

We will be happy to add your success story using CatBoost to this list. Send us a pull request if you want to include your case here.


## Use cases
* The Large Hadron Collider beauty (LHCb) experiment uses [CatBoost](https://catboost.ai/news#particle_identification).
* [Careem](https://careem.com/), the leading ride-hailing platform for the greater Middle East, uses CatBoost for their [Destination Prediction Service](https://blog.careem.com/en/careems-destination-prediction-service/).
* CatBoost is used in [Kaggle Kernels](https://www.kaggle.com/kernels?sortBy=relevance&group=everyone&search=catboost&page=1&pageSize=100) to solve data science challenges.

## Tools using CatBoost
* [auto_ml](https://github.com/ClimbsRocks/auto_ml) - Automated machine learning for production and analytics. Lets you focus on the fun parts of ML, while outputting production-ready code, and detailed analytics of your dataset and results. Includes support for CatBoost and other ml libraries.
* [mljar-supervised](https://github.com/mljar/mljar-supervised) - An Automated Machine Leaning (AutoML) open-source python package for binary and mutliclass classification and regression ML tasks. It is using CatBoost algorithm among many others. It provides explanations for CatBoost models: feature importance computed by permutation method and SHAP explanations: feature importance, dependency plots and decision plots (computed with CatBoost internals).