CreditCue is a predictive analysis tool designed to assist in credit risk assessment. This program utilizes machine learning techniques to analyze customer data and predict the likelihood of a customer making a purchase based on their age and salary.
- Prediction: Given a CSV file containing customer data (age and salary), CreditCue predicts whether each customer is likely to make a purchase.
- User-Friendly Interface: CreditCue provides a simple and intuitive interface for users to input their data and view the prediction results.
- Scalable: The program is designed to handle large datasets efficiently, making it suitable for real-world applications.
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Clone the repository: git clone https://github.com/shadowcone/CreditCue.git
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Install the required dependencies: pip install pandas scikit-learn
- Run the
main.pyscript: python3 main.py - Enter the path to the CSV file containing customer data when prompted.
- Click the "Predict" button to generate predictions.
- View the prediction results displayed in the table.
Contributions are welcome! If you find any bugs or have suggestions for improvements, please open an issue or create a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.