feat: implement ML filter with LightGBM for trading signal validation

- Added MLFilter class to load and evaluate LightGBM model for trading signals.
- Introduced retraining mechanism to update the model daily based on new data.
- Created feature engineering and label building utilities for model training.
- Updated bot logic to incorporate ML filter for signal validation.
- Added scripts for data fetching and model training.

Made-with: Cursor

requirements.txt

@@ -8,3 +8,7 @@ pytest-asyncio>=0.24.0
 aiohttp==3.9.3
 websockets==12.0
 loguru==0.7.2
+lightgbm>=4.3.0
+scikit-learn>=1.4.0
+joblib>=1.3.0
+pyarrow>=15.0.0