Stock Price Prediction

This project aims to predict stock prices using the Prophet model. It includes a Streamlit dashboard for displaying historical data and making predictions for the next working day.

Prerequisites

• Python 3.7 or higher
• Streamlit
• Prophet
• Pandas
• Scikit-learn

Installation

1. Clone the repository: git clone https://github.com/your-username/stock-price-prediction.git
2. Change to the project directory: cd stock-price-prediction
3. Install the required dependencies: pip install -r requirements.txt

Usage

1. Run the Streamlit app: streamlit run app.py

2. Open your web browser and navigate to http://localhost:8501 to access the application.

The app displays historical data and predicts the stock prices for the next working day.

Customization

• To use your own historical data, replace the get_data() function in GetData.py with your data retrieval logic.

• To train the Prophet models on your own data, modify the prophet.py file. You can customize the model training and evaluation process.

License

This project is licensed under the MIT License.

Feel free to use and modify the code according to your needs.

Acknowledgments

• Prophet - A forecasting library by Facebook Research.
• Streamlit - An open-source app framework for machine learning and data science.
• Pandas - A powerful data manipulation and analysis library.
• Scikit-learn - A machine learning library for Python.

Contact

For any inquiries or suggestions, please feel free to reach out to ([email protected]).