A curated list of data mining papers about fraud detection.

iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for Anomaly Detection in credit card transactions data

Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

Analysis of credit card fraud data

Implementation of feature engineering from Feature engineering strategies for credit card fraud

Credit Card Fraud Detection Project with Code and Documents

Anomaly Detection Pipeline with Isolation Forest model and Kedro framework

Classification of fraudulent credit card transactions.

A credit card mass checker tool that could check a card's validity based on luhn algorithm.

{PySpark, R, Python}: Several Data Science projects

Python app for detecting credit card frauds using a graph database

Credit card fraud is a significant problem, with billions of dollars lost each year. Machine learning can be used to detect credit card fraud by identifying patterns that are indicative of fraudulent transactions. Credit card fraud refers to the physical loss of a credit card or the loss of sensitive credit card information.

Monotonic Optimal Binning algorithm is a statistical approach to transform continuous variables into optimal and monotonic categorical variables.

💳 Creates a new gym environment for credit-card anomaly detection using Deep Q-Networks (DQN) and leverages Open AI's Gym toolkit to allocate appropriate awards to the RL agent.

Credit Risk Analysis with Machine Learning

Anomaly detection using isolation forest

An attempt to detect fraud in online transaction in deep neural network using pytorch

Learn to use Support Vector Machines in Python(sklearn) and R

Full Stack Credit Card Fraud Detection Using Machine Learning with Code and Documents Plus Youtube Explanation Video