Popular GitHub Repositories for Xgboost

A python library for decision tree visualization and model interpretation.

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

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.).

Provide an input CSV and a target field to predict, generate a model + code to run it.

Distributed ML Training and Fine-Tuning on Kubernetes

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

AI比赛相关信息汇总

? The experiment tracker for foundation model training

An extension of XGBoost to probabilistic modelling

用户贷款风险预测

Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

A Scala feature transformation library for data science and machine learning

pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks

Real time eye tracking for embedded and mobile devices.

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

Machine Learning University: Decision Trees and Ensemble Methods

A project to deploy an online app that predicts the win probability for each NBA game every day. Demonstrates end-to-end Machine Learning deployment.

AI100文本分类竞赛代码。从传统机器学习到深度学习方法的测试

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