This project aims to predict whether a credit card transaction is fraudulent or legitimate in real-time. It provides a web interface to submit transaction data and receive a fraud probability score.

Dataset

The model will be trained on the Kaggle Credit Card Fraud Dataset.

Model

The initial implementation uses a Logistic Regression model as a baseline.

API Usage

/predict: POST endpoint that accepts transaction data and returns a fraud probability.
/health: GET endpoint to check service status.

Future Improvements

Implement more advanced models (Random Forest, XGBoost).
Add user authentication.
Deploy to a cloud environment.