Popular GitHub Repositories for Random Forest

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 python library for decision tree visualization and model interpretation.

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.).

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

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

A python library to build Model Trees with Linear Models at the leaves.

Compendium of free ML reading resources

Machine Learning University: Decision Trees and Ensemble Methods

An end-to-end machine learning and data mining framework on Hadoop

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

InfiniteBoost: building infinite ensembles with gradient descent

Machine learning tool to detect landslides from optical satellite imagery

Machine learning semantic segmentation - Random Forest, SVM, GBC

A Streamlit based application to predict future Stock Price and pipeline to let anyone train their own multiple Machine Learning models on multiple stocks to generate Buy/Sell signals. This is a WIP and I will keep on adding new ideas to this in future.

This repository contains all the Lab and Assignments from Andrew NG Machine Learning Specialization Course on Coursera.

Random Forests in Apache Spark