Popular GitHub Repositories for Ramdom Forest

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

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

A python library for decision tree visualization and model interpretation.

A collection of research papers on decision, classification and regression trees with implementations.

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Text Classification Algorithms: A Survey

利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

A curated list of Best Artificial Intelligence Resources

A curated list of gradient boosting research papers with implementations.

A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Machine Learning inference engine for Microcontrollers and Embedded devices

A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.

Machine Learning library for the web and Node.

? Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

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