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Credit Card Fraud Detection System

Flask application for feature analysis involving fraud detection and a recommender system for fraud protection services. Incorporating the use of SOTA machine learning algorithms and deep learning techniques.

Table of Contents

Installation

  1. Clone the repository - git clone
  2. Install the requirements - pip install -r requirements.txt
  3. Run the application - python app.py

Usage

  1. Run the application - python app.py
  2. Navigate to the application's URL - http://localhost:5000/
  3. Upload a CSV file - transactions.csv
  4. Select the target column - Class
  5. Select the features to analyze - Amount, Is Fraud, etc.
  6. Click the "Analyze" button - Analyze

Contributing

  1. Fork the repository - ``
  2. Create a new branch - git checkout -b new-branch
  3. Commit your changes - git commit -m "New branch"
  4. Push your changes - git push origin new-branch
  5. Submit a pull request - ``

License

MIT

Credits

Author

Jason Robinson