• This project is a full-stack AI-based fraud detection system that analyzes credit card transactions to detect fraudulent activities. The system features a React frontend, Node.js backend, and Flask-based machine learning model.

Features

• Real-time fraud detection using a trained Random Forest model.
• RESTful API for seamless backend communication.
• Interactive dashboard built with React.
• Scalable and consistent deployment using Docker and AWS EC2.
• Robust unit testing with Jest and Pytest.

Tech Stack

• Frontend: React, Nginx
• Backend: Node.js, Express, MongoDB
• Machine Learning: Python, Flask, Random Forest
• Deployment: Docker, AWS EC2
• Testing: Jest, Pytest

Instalation and Setup

1. git clone https://github.com/ahing1/Fraud-Detector.git
2. cd Fraud-Detection
3. docker-compose build --no-cache
4. docker-compose up

Usage

• Use the dashboard to upload and analyze transactions
• View profile with users information