Popular GitHub Repositories for 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.

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

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

A curated list of gradient boosting research papers with implementations.

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

AI比赛相关信息汇总

本人多次机器学习与大数据竞赛Top5的经验总结，满满的干货，拿好不谢

A full pipeline AutoML tool for tabular data

Amazon SageMaker Local Mode Examples

Machine Learning University: Decision Trees and Ensemble Methods

R package for automation of machine learning, forecasting, model evaluation, and model interpretation

IJCAI-18 阿里妈妈搜索广告转化预测初赛方案

A 100%-Julia implementation of Gradient-Boosting Regression Tree algorithms

Automatic machine learning for tabular data. ???

AutoFlow : Automatic machine learning workflow modeling platform

Tennis AI to predict the winner in ATP matches with 3 different models and a web UI

Analyzing the HR Criteria of a Company and how they promote their Employees and keep Balance between them using Data Analytics, Data Visualizations, and Machine Learning Models for Classification Purposes.

Easy Custom Losses for Tree Boosters using Pytorch

Save Your Time ! Automated Interpretable Machine Learning Workflow

A binary classification model is developed to predict the probability of paying back a loan by an applicant. Customer previous loan journey was used to extract useful features using different strategies such as manual and automated feature engineering, and deep learning (CNN, RNN). Various machine learning algorithms such as Boosted algorithms (XGBoost, LightGBM, CatBoost) and Deep Neural Network are used to develop a binary classifier and their performances were compared.