- Introduced `RegimeReversionStrategy` for ML-based regime detection and mean reversion trading.
- Added feature engineering and model training logic within the new strategy.
- Removed the deprecated `regime_detection.py` file to streamline the codebase.
- Updated the strategy factory to include the new regime strategy configuration.
- Introduced `CryptoQuantClient` for fetching data from the CryptoQuant API.
- Added `regime_detection.py` for advanced regime detection analysis using machine learning.
- Updated dependencies in `pyproject.toml` and `uv.lock` to include `scikit-learn`, `matplotlib`, `plotly`, `requests`, and `python-dotenv`.
- Enhanced `.gitignore` to exclude `regime_results.html` and CSV files.
- Created an interactive HTML plot for regime detection results and saved it as `regime_results.html`.
