Skip to content

Latest commit

 

History

History
36 lines (28 loc) · 1.51 KB

README.md

File metadata and controls

36 lines (28 loc) · 1.51 KB
Raw

Online Transaction Fraud Detection

License: MIT Python 3.8+

Overview

The Online Transaction Fraud Detection system is a machine learning project designed to identify fraudulent activities in online transactions. It uses a combination of rule-based systems and anomaly detection algorithms in Artificial Intelligence to flag suspicious transactions for further review.

Key Features

  • Real-time monitoring: The system can monitor transactions in real-time to identify potential fraud.
  • Anomaly detection: It uses advanced algorithms to detect anomalies that may indicate fraudulent behavior.
  • User-friendly interface: A simple and intuitive user interface for non-technical users.

Getting Started

To get started with the project, follow these steps:

Prerequisites

  • Python 3.8 or higher
  • Libraries: numpy, pandas, scikit-learn, Pytorch, PyQt5, torchvision, etc.
  • Or install from requirement: 
    pip install -r requirement.txt

Installation

  1. Clone the repository: 
    git clone https://github.com/YapWH/Fraud-Detection.git
  2. Open the folder and run the MCYIC.py file. 
    python MCYIC.py

Contribution