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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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.
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
A MNIST-like fashion product database. Benchmark :point_down:
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
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.
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.
A collection of research papers on decision, classification and regression trees with implementations.
A curated list of community detection research papers with implementations.
Interpretability and explainability of data and machine learning models
A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
A research toolkit for particle swarm optimization in Python
Earth observation processing framework for machine learning in Python
Plug and Play Language Model implementation. Allows to steer topic and attributes of GPT-2 models.
A curated list of gradient boosting research papers with implementations.
OpenChem: Deep Learning toolkit for Computational Chemistry and Drug Design Research
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Tools for computational pathology
Docker image gathering packers and tools for making datasets of packed executables and training machine learning models for packing detection
Cryptographic Dataset Generation & Modelling Framework