Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
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.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
ThunderGBM: Fast GBDTs and Random Forests on GPUs
Natural Gradient Boosting for Probabilistic Prediction
A fast xgboost feature selection algorithm
open-source agentic AI data assistant for the next generation of AI + Data products.
6 captures since 2026-05-22
