RaimbekovA/bank-card-fraud-detection-using-machine-learning
Bank card fraud detection using machine learning. Web application using Streamlit framework
This application helps financial analysts and fraud prevention specialists analyze bank transactions to identify suspicious activity. You input a dataset of credit card transactions, and it provides a report with graphs, tables, and a comparison of three machine learning algorithms' effectiveness in detecting fraud. You can also manually verify individual transactions.
No commits in the last 6 months.
Use this if you need a quick way to compare different fraud detection models and analyze bank transaction data in an interactive web application.
Not ideal if you require a production-ready, highly optimized, and scalable fraud detection system for real-time transaction processing.
Stars
17
Forks
4
Language
Python
License
—
Category
Last pushed
Jun 26, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/RaimbekovA/bank-card-fraud-detection-using-machine-learning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
GoogleCloudPlatform/fraudfinder
Fraudfinder: A comprehensive lab series on how to build a real-time fraud detection system on...
benedekrozemberczki/awesome-fraud-detection-papers
A curated list of data mining papers about fraud detection.
jube-home/aml-fraud-transaction-monitoring
Open source AML and Fraud Detection using Machine Learning for Real-Time Transaction Monitoring
aws-solutions-library-samples/fraud-detection-using-machine-learning
Setup end to end demo architecture for predicting fraud events with Machine Learning using...
curiousily/Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for...