A game theoretic approach to explain the output of any machine learning model.
- interpretability
- machine-learning
- deep-learning
- gradient-boosting
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A game theoretic approach to explain the output of any machine learning model.
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
Bitmap & tilemap generation from a single example with the help of ideas from quantum mechanics
The fastai book, published as Jupyter Notebooks
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Translated✅ (Completed) Super comprehensive deep learning notes [Tudui PyTorch] [Li Mu Dive into Deep Learning] [Andrew Ng Deep Learning] [Dafei LLM Agent]
TranslatedPArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (Core framework of 'PaddlePaddle' (飞桨, Feijiang), for deep learning & machine learning: high-performance single-machine and distributed training, and cross-platform deployment)
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
Universal LLM Deployment Engine with ML Compilation
Learn OpenCV : C++ and Python Examples
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
TranslatedCollection of CVPR 2026 papers and open-source projects
Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.
A machine learning-based video super resolution and frame interpolation framework. Est. Hack the Valley II, 2018.
🚀 A curated collection of AI engineering resources, roadmaps, tools, and projects covering LLMs, RAG, AI Agents, MCP, fine-tuning, evaluations, and production AI systems.
YC (S26) | Open Computer History | Continuously record your company computer work, map your workflows, help you find work worth automating, and power your agents' context
Translated100-Days-Of-ML-Code Chinese version
ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Best Practices on Recommendation Systems
☁️ Build multimodal AI applications with cloud-native stack