Popular GitHub Repositories for Gradient Boosting Machine

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.).

Performance of various open source GBM implementations

Building Decision Trees From Scratch In Python

Programmable Decision Tree Framework

NTUEE Machine Learning, 2017 Spring

Modified XGBoost implementation from scratch with Numpy using Adam and RSMProp optimizers.

This repository covers h2o ai based implementations

Feature Crawler used for a Fraud Prevention competition

Kernels for machine learning problems

A challenge to create a model that uses data from the first 24 hours of intensive care to predict patient survival