stockGenie

A price prediction application using trained on live stock price data and deployed using Streamlit.

Features

• Real-time stock price data fetching
• Live model training & prediction
• Interactive visualizations
• Model performance metrics

Installation

pip install -r requirements.txt

Usage

streamlit run app.py

Testing

pytest tests/

Project Structure

stock_predictor/
├── src/                # Source code
│   ├── data/           # Data handling
│   ├── logs/           # Logs
│   ├── models/         # ML models
│   ├── utils/          # Utilities
│   └── config.py       # Configuration
├── tests/              # Unit tests
├── app.py              # Streamlit app
├── requirements.txt    # Dependencies
└── README.md           # Documentation

Contributing

Contributions are welcome! Here's how you can help:

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Future Tasks

• Add progress bars (for model training)
• Add more data sources
• Try SOTA ML models
• Refine visualizations

---

Made with 💙 by Argish