[🔥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
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.
Stock AI Trader: 1-stop platform for learning, sim & live trading. Covers: stock basics, strategies, LLMs, factor mining, ML/DL/RL, graph nets, HFT, C++ deploy & JoinQuant code. 股票AI操盘手:一站式学习、模拟、实盘平台。涵盖:股票基础、策略、大模型、因子挖掘、机器学习/深度学习/强化学习、图网络、高频交易、C++部署及聚宽代码。
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
Everything you need to know to build your own RAG application
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
Bayesian optimization in PyTorch
Massively parallel rigidbody physics simulation on accelerator hardware.
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
Benchmarking Knowledge Transfer in Lifelong Robot Learning
Practical course about Large Language Models.
A group of notebooks and other files which can help you learn AI from scratch.
Python tutorials in both Jupyter Notebook and youtube format.
Evaluating and reproducing real-world robot manipulation policies (e.g., RT-1, RT-1-X, Octo) in simulation under common setups (e.g., Google Robot, WidowX+Bridge) (CoRL 2024)
Code examples for Robotics, Vision & Control 3rd edition in Python
Notebook-based book "Introduction to Robotics and Perception" by Frank Dellaert and Seth Hutchinson
EDA-Q is a full-stack electronic design automation (EDA) tool for quantum chip design, supporting both superconducting and trapped-ion quantum computing architectures. The platform enables researchers and engineers to efficiently design, simulate, and optimize quantum chips.
Module_5_Data Handling & Visualization_6_AI Applications & Mini Project
[CoRL 2026] EgoWAM: World Action Models Beyond Pixels with In-the-Wild Egocentric Human Data
A practical toolkit for process-level robot evaluation with Process Reward Models (PRMs).
Independent quantitative finance research project comparing U.S. and Kazakhstan equity markets using Python and portfolio theory.