An advanced deep learning model for predicting Bitcoin prices using LSTM neural networks and technical analysis.
- Real-time Bitcoin price data fetching via
yfinance
- Advanced technical indicators (MA, RSI, MACD)
- LSTM neural network with dropout and batch normalization
- Comprehensive visualization suite
- Multiple performance metrics
Metric | Value |
---|---|
MSE | 51,790,828 |
RMSE | 7,334 |
MAE | 4,434 |
R² Score | 0.863 |
Accuracy | 91.67% |
git clone https://github.com/yourusername/bitcoin-price-predictor.git
cd bitcoin-price-predictor
pip install -e .
python -m bitcoin_predictor.main
python -m bitcoin_predictor.main \
--symbol BTC-USD \
--period max \
--sequence-length 60 \
--batch-size 32 \
--epochs 100
python -m unittest discover bitcoin_predictor/tests
The model generates several visualizations in the visualizations
directory:
- Training history plots
- Prediction vs Actual comparisons
- Feature correlation heatmaps
- Error distribution analysis
- Rolling metrics plots
- numpy
- pandas
- scikit-learn
- tensorflow
- yfinance
- matplotlib
- seaborn
- python-graphviz
The project uses Python's logging framework. Logs are stored in the logs
directory with timestamped filenames.
- Fork the repository
- Create a feature branch
- Commit your changes
- Push to the branch
- Create a Pull Request
This project is licensed under AGPL-3.0