This project is aimed at analyzing and predicting stock prices using historical data.
- Data collection: Retrieve stock price data from various sources.
- Data preprocessing: Clean and preprocess the collected data.
- Visualization: Generate visualizations to analyze stock price trends.
- Statistical analysis: Perform statistical analysis on stock price data.
- Prediction models: Implement machine learning models to predict future stock prices.
- Evaluation: Evaluate the performance of prediction models.
- Clone the repository:
git clone https://github.com/your-username/STOCK_PRICE.git - Install the required dependencies:
pip install
- Collect stock price data using the provided data collection module.
- Preprocess the collected data to remove outliers and handle missing values.
- Visualize the data using the visualization module to gain insights.
- Perform statistical analysis on the data to identify patterns and trends.
- Train and evaluate prediction models to forecast future stock prices.
Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.
This project is licensed under the MIT License.
For any inquiries or questions, please contact [email protected].