Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
Repository Index
47,133 repositories indexed
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⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
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.
[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
Workflow Engine for Kubernetes
《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
Nmap - the Network Mapper. Github mirror of official SVN repository.
Gaining advanced insights from Git repository history.
3,516 curated Figure 1 / teasers from ICLR, ICML, NeurIPS, CVPR, ACL, AAAI (2023-2026), with tier badges and FigureForge retrieval-augmented figure drafting
Interactive, source-linked ML workflow diagrams written by your coding assistant (Copilot, Codex or Claude Code) and opened in VS Code.
Tools for computational pathology
Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk
Machine Learning and Digital Signal Processing for MicroPython
⚡ Open-source software for deep learning-based digital pathology
Examples of Tensorflow Lite on Android
:mega: Python library for audio augmentation
Golem Image Classifier is built using the Service API of Yapapi to interact with the Golem Network (golem.network). Built as part of a Gitcoin Bounty
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.