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A high-performance gradient boosting library with best-in-class handling of categorical features and support for CPU/GPU training.
A Python library for time series forecasting using scikit-learn compatible machine learning models.
A curated collection of gradient boosting research papers with implementations from top machine learning conferences.
Automatically builds high-performance interpretable machine learning models with minimal features using a single line of code.
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