CatBoost is a high-performance open source library for gradient boosting on decision trees


Cloudflare's Protection Against Bots Employs CatBoost

March 7, 2019

Training with CatBoost on a CPU/GPU cluster with a dataset of trillion requests helps to identify malicious bot traffic.

Read the full version

Careem's Destination Prediction Service uses CatBoost

February 20, 2019

Careem, the leading ride-hailing platform for the greater Middle East, explained how CatBoost helps predicting their customer next move.

Read the full version

CatBoost Enables Fast Gradient Boosting on Decision Trees Using GPUs

December 18, 2018

Gradient boosting benefits from training on huge datasets. In addition, the technique is efficiently accelerated using GPUs. Read details in this post.

Read the full version

CatBoost papers on NeurIPS 2018

December 17, 2018

On December 2018, on NeurIPS conference in Montreal, Yandex team presented two papers related to CatBoost, an open-source machine learning library developed by Yandex.

Read the full version

0.10.x and 0.9.x releases review

November 2, 2018

CatBoost team continues to make a lot of improvements and speedups. What new and interesting have we added in our two latest releases and why is it worth to try CatBoost now? We'll discuss it in this post.

Read the full version

New ways to explore your data

April 20, 2018

New superb tool for exploring feature importance, new algorithm for finding most influential training samples, possibility to save your model as cpp or python code and more. Check CatBoost v0.8 details inside!

Read the full version