StockPredict is a project aimed at predicting stock prices using linear regression. By analyzing historical data such as past stock prices, trading volume, and market trends, the model attempts to forecast future stock prices. This README provides an overview of the project, its features, installation instructions, and usage guidelines.
Utilizes linear regression for stock price prediction.
Analyzes historical stock prices, trading volume, and market trends.
Trains the model on historical data and evaluates against test data.
Provides forecasts for future stock prices based on learned patterns and trends.
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Clone the repository to your local machine:
git clone https://github.com/RAJESHVHANKADE/StockPredict-Forecasting-Stock-Prices-with-Linear-Regression
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Install the required dependencies using pip:
pip install -r requirements.txt
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Navigate to the project directory:
cd StockPredict
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Run the application:
python predict.py
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Input historical data for analysis.
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Receive forecasts for future stock prices.
Contributions are welcome! If you'd like to contribute to StockPredict, please fork the repository and submit a pull request with your changes.
This project is licensed under the MIT License - see the LICENSE file for details.
For any inquiries or feedback, please contact https://www.linkedin.com/in/rajesh-vhankade-ab7627215/ & vhankadenrajesh@gmail.com.