37 lines
1.1 KiB
Markdown
37 lines
1.1 KiB
Markdown
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# AI / Machine Learning
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ONNX-based price-action models for MetaTrader 5.
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## Projects
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| Directory | Symbol / TF | Notes |
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|-----------|-------------|-------|
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| [`xauusd_h1/`](xauusd_h1/) | XAUUSD H1 | Action classification EA |
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| [`xauusd_m15/`](xauusd_m15/) | XAUUSD M15 | Shorter horizon |
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| [`eurusd1h/`](eurusd1h/) | EURUSD H1 | |
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| [`eurusd1min/`](eurusd1min/) | EURUSD M15 model | |
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| [`btcusd1min/`](btcusd1min/) | BTCUSD M1 | |
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| [`rsi-divergence/`](rsi-divergence/) | Divergence detector + EA |
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| [`dummy/`](dummy/) | XAUUSD sandbox | Full train → ONNX → backtest walkthrough |
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## Quick start (sandbox)
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```bash
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cd ai/dummy
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pip install -r requirements.txt
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python train_onnx_model.py
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python quick_backtest.py
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```
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Trained artifacts (`models/*.onnx`, `*.pkl`) are **gitignored** — generate locally after clone.
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## MQL5 integration
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Each project includes an `.mq5` EA that loads ONNX via `#resource` or file path. See per-folder `README.md` and `MT5_SETUP.md` (dummy).
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## Requirements
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- Python 3.10+
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- `MetaTrader5`, `onnxruntime`, `scikit-learn`, `pandas`, `numpy`
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- Local MT5 terminal with history for your symbol
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