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.

Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

A library for debugging/inspecting machine learning classifiers and explaining their predictions

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.

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

QuantMind（量化大脑）开源版是一款面向个人开发者与投研团队的 AI 原生多市场量化交易平台。深度集成微软 Qlib、RD-Agent 因子演化与 TradingAgents 多智能体投研，提供从 300+ 维因子挖掘、13 种机器学习与深度学习模型工场、Optuna 自动调参、Qlib 高性能回测、截面批量推理、7x24 实时舆情情绪分析，到通达信深度联动（板块推送/预警雷达/闪电下单）与实盘模拟交易的完整闭环。全面支持 A股、港股、美股、期货及区块链。系统采用 Docker Compose 一键私有化部署，数据与模型完全本地化，保障策略隐私，功能零门槛无限制。

Scalable machine 🤖 learning for time series forecasting.

Scalable Python DS & ML, in an API compatible & lightning fast way.

A curated list of gradient boosting research papers with implementations.

An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more

Python Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch

Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference.

Impress your boss with interactive Decision Tree visualization

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

REST web service for the true real-time scoring (<1 ms) of Scikit-Learn, R and Apache Spark models

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

Antivirus software written in Python and C++ that blocks threats through Machine Learning and behavioral monitoring!