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sachink2010/AutomatedStockTrading-DeepQ-Learning
Automated stock trading with deep Q-learning
What it is
An automated stock trading project based on deep Q-learning. An agent is trained to learn buy and sell decisions so that trading can be carried out by the algorithm. Developers and researchers who want to explore reinforcement learning applied to stock trading can study the notebooks. It is an educational project, and models trained this way need careful out-of-sample evaluation before any real use.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Developers |
|---|---|
| Used for | Strategy research, Backtesting |
| Markets | US equities |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | Low practical value |
| Cost | Free and open source |
| Hardware | GPU optional |
| Maintenance | No commits in over six months |
GitHub stars, last 30 days
Daily snapshots since 2026-09-28 (up to 30 days): +6 over the period, now 302. Gaps mean no snapshot was taken that day.
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market
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