This project provides a comprehensive stock market analysis and price prediction system. It processes historical stock data, applies machine learning models for forecasting, and serves predictions via a web API.
Loads historical stock price data from CSV files.
Updates stock data dynamically using automated scripts.
Implements LSTM, GRU, and Prophet models for stock price prediction.
Uses pre-trained models for forecasting future trends.
Serves stock data and predictions through API endpoints.
Built using Flask for real-time data access.
Generates stock insights using stock_dashboard.py.
Web-based visualization using index.html.
Includes scripts to automate stock data updates.
Performs data cleaning and transformation for analysis.
- Real-time Stock Analysis – Provides updated market insights.
- Predictive Analytics – Helps in forecasting future trends.
- Web Integration – Can be accessed via a web interface.
- Data-Driven Decision Making – Useful for investors and traders.
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Clone the repository: git clone <repository_url>
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Navigate to the project folder: cd project_folder
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Install dependencies: pip install -r requirements.txt
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Run the API Server: python api.py
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Fetch Live Stock Data: python update_stock_data.py
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Run Dashboard: streamit run dashboard.py
This project is licensed under the MIT License.