{
  "name": "Broker API Hub: Trading repositories on GitHub",
  "licence": "CC BY 4.0",
  "cite": "Broker API Hub, Trading repositories on GitHub, openbrokerapi.com/data",
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      "description": "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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        "note": "The README puts the code under MIT and reserves all rights in the book's content. The only diagram is of the book.",
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    {
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        "shows": "A diagram of the reinforcement learning loop the library is built around: an agent reads a state, chooses to sell, hold or buy, and the environment returns a reward",
        "alt": "Flow diagram. A State box (balance, shares, prices, technical indicators) feeds a Trading Agents box listing DQN, DDPG, PPO, SAC, A2C, TD3 and multi-agent DDPG. The agents send an Action (sell, hold or buy) to an Environment box, which returns a Reward (profit or loss) and the next state.",
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    {
      "id": "ta-lib--ta-lib-python",
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    {
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    {
      "id": "stocksharp--stocksharp",
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    {
      "id": "polakowo--vectorbt",
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      "description": "The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.",
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    {
      "id": "kernc--backtesting.py",
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