The Fraud Detection project for E-commerce and Banking Transactions aims to significantly improve the identification of fraudulent activities within these sectors. It focuses on developing advanced machine learning models that analyze transaction data, employ sophisticated feature engineering techniques, and implement real-time monitoring systems to achieve high accuracy in fraud detection.

1. Exploratory Data Analysis (EDA)
2. Model Building and Training
3. Model Explainability Using SHAP
4. Model Deployment and API Development
5. Contributing
6. License

After training and testing six models (three for each dataset), we selected the following models:

Generated 3 new instances and sent a request to the fraud detection model api.

Contributions are welcome! Please fork the repository and submit a pull request.

This project is licensed under the MIT License. See the LICENSE file for details.