A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

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• Updated Nov 12, 2026
• C++

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.

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• Updated Nov 12, 2026
• C++

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

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• Updated Dec 28, 2025
• Jupyter Notebook

🍊 📊 💡 Orange: Interactive data analysis

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• Updated Nov 8, 2026
• Python

Python code for common Machine Learning Algorithms

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• Updated Jun 5, 2025
• Jupyter Notebook

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

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• Updated May 22, 2023
• Jupyter Notebook

A python library for decision tree visualization and model interpretation.

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• Updated Jan 2, 2026
• Jupyter Notebook

For extensive instructor led learning

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• Updated Oct 31, 2022
• Jupyter Notebook

Text Classification Algorithms: A Survey

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• Updated Apr 1, 2025
• Python

General Assembly's 2015 Data Science course in Washington, DC

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• Updated Jun 5, 2024
• Jupyter Notebook

A curated list of Best Artificial Intelligence Resources

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• Updated Sep 19, 2026
• Jupyter Notebook

Impress your boss with interactive Decision Tree visualization

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• Updated Aug 11, 2026
• JavaScript

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

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• Updated May 19, 2026
• Python

Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference.

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• Updated Apr 16, 2026
• Python

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

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• Updated Nov 11, 2026
• C++

Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

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• Updated May 1, 2023
• Python

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical features support for Python

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• Updated May 13, 2026
• Python

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

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• Updated Jul 3, 2024
• Go

Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.

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• Updated Jan 1, 2026
• Python

🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!

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• Updated Aug 25, 2023
• Python