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.
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🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
PyTorch Tutorial for Deep Learning Researchers
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
☁️ Build multimodal AI applications with cloud-native stack
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
A MNIST-like fashion product database. Benchmark :point_down:
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
Hierarchical Reasoning Model Official Release
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
AutoML library for deep learning
Scalable and user friendly neural :brain: forecasting algorithms.
Visual localization made easy with hloc
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
A best practice for tensorflow project template architecture.
Accelerated deep learning R&D
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Automatic architecture search and hyperparameter optimization for PyTorch
A curated list of community detection research papers with implementations.
:unlock: Lip Reading - Cross Audio-Visual Recognition using 3D Architectures
Interpretability and explainability of data and machine learning models