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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Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
The #1 AI Harness for Building Resumes, PDFs, Cover Letters & more, locally with 100+ LLMs support.
☁️ 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.
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 curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome.
A MNIST-like fashion product database. Benchmark :point_down:
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
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.
An autoML framework & toolkit for machine learning on graphs.
A curated list of gradient boosting research papers with implementations.