Fraudshield
A machine learning-powered web application for detecting fraudulent credit card transactions. Built with XGBoost, Flask, and a modern Tailwind CSS + React-inspired UI. Includes real-time predictions, dark mode toggle, animated particles background, and fully responsive design.
FraudShield - Credit Card Fraud Detection
A machine learning-based application to detect fraudulent credit card transactions in real-time.
š Project Overview
FraudShield is a web application designed to identify potentially fraudulent credit card transactions using machine learning algorithms. The system analyzes transaction features and provides instant feedback on whether a transaction is likely to be legitimate or fraudulent.
š¬ Demo Video
Watch the project demonstration here:
š View Demo Video
āØ Features
- š Real-time credit card fraud detection
- š User-friendly web interface
- š¤ Machine learning model for accurate fraud prediction
- š Detailed results visualization
- š Development mode for testing and debugging
š ļø Technologies Used
- Python
- Flask
- Machine Learning (Scikit-learn, XGBoost)
- Pandas & NumPy
- HTML / CSS
- TailwindCSS
šø Screenshots
Screenshot 1:
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Screenshot 5:
š Installation & Setup
1. Clone the repository:
git clone https://github.com/Khushi04092004/FraudShield.git
cd FraudShield
