A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
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A collection of research papers on decision, classification and regression trees with implementations.
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
CatBoost tutorials repository
A curated list of gradient boosting research papers with implementations.
CatBoost a fast, scalable, high performance Gradient Boosting on Decision Trees library. Golang using Cgo for blazing fast inference CatBoost Model 🚀