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

Dockerfile

@@ -11,7 +11,7 @@ RUN pip install --no-cache-dir -r requirements.txt
 
 COPY . .
 
-RUN mkdir -p logs
+RUN mkdir -p logs models data
 
 ENV PYTHONUNBUFFERED=1
 ENV PYTHONDONTWRITEBYTECODE=1