A Machine Learning based web application that predicts whether a financial transaction is fraudulent or normal.
The application takes transaction details such as amount, city population, latitude, and longitude and uses a trained ML model to detect fraud.
Try the application here:
https://ml-fraud-detection-system.streamlit.app/
Online financial fraud is increasing rapidly.
This project builds a machine learning model that can identify suspicious transactions.
The system uses transaction data to classify transactions into:
• Normal Transaction
• Fraudulent Transaction
The model is integrated into a web application using Streamlit.
• Predicts fraudulent transactions
• Simple web interface
• Real-time prediction
• Machine learning model integration
• Deployed online using Streamlit Cloud
Python
Pandas
Scikit-learn
Streamlit
Machine Learning
GitHub