Fraud-Detection-Handbook/fraud-detection-handbook
Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook
This handbook helps students and professionals tackle the complex problem of credit card fraud detection using machine learning. It provides reproducible methods and code examples, turning raw transaction data into actionable insights for identifying fraudulent activities. This resource is for anyone working to improve fraud detection systems.
683 stars. No commits in the last 6 months.
Use this if you are a data practitioner or data scientist focused on applying machine learning to detect credit card fraud, especially with sequential data or imbalanced classification challenges.
Not ideal if you are looking for a general machine learning textbook unrelated to financial fraud or if you need a plug-and-play software solution.
Stars
683
Forks
210
Language
Jupyter Notebook
License
—
Category
Last pushed
Feb 07, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Fraud-Detection-Handbook/fraud-detection-handbook"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Compare
Related frameworks
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
safe-graph/DGFraud
A Deep Graph-based Toolbox for Fraud Detection
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...