Machine LearningTabular Machine LearningOn this pageTabular Machine LearningTreesGitHub - catboost/catboost: 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.GitHub - microsoft/LightGBM: 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.GitHub - dmlc/xgboost: 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 DataFlowGitHub - sb-ai-lab/Py-Boost: Python based GBDT implementation on GPU. Efficient multioutput (multiclass/multilabel/multitask) trainingGitHub - sb-ai-lab/sketchboost-paper: Repository to reproduce SketchBoost paper experiments