There are 24 repositories under credit-card-fraud topic.
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
Classification of fraudulent credit card transactions.
Anomaly Detection Pipeline with Isolation Forest model and Kedro framework
Credit Card Fraud Detection Project with Code and Documents
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
Monotonic Optimal Binning algorithm is a statistical approach to transform continuous variables into optimal and monotonic categorical variables.
Anomaly detection using isolation forest
An attempt to detect fraud in online transaction in deep neural network using pytorch
đź’ł 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.
System to tell apart the transaction was from the real user who owns the credit card or the transaction was from the stolen credit card.
Apply 7 common Machine Learning Algorithms to detect fraud, while dealing with imbalanced dataset
Ensemble Learning Techniques Tutorial with Credit Card Fraud
Using simple logistic regression to predict credit card fraud transactions
This project commissions to examine the 100,000 credit card application data, detect abnormality and potential fraud in the dataset. All data manipulation and analysis are conducted in R. Featured analysis methods include Principal Component Analysis (PCA), Heuristic Algorithm and Autoencoder.
Python Data Analytics, Machine Learning & Natural Language Processing
This is a classification problem to detect or classify the fraud with label 0 or 1. Class with label 1 means fraud is detected otherwise 0. The biggest challenge is to handle the imbalanced data set.
Credit Card Fraud Detection using machine learning
Full Stack Credit Card Fraud Detection Using Machine Learning with Code and Documents Plus Youtube Explanation Video
In this project, I explore different methods for detecting credit card fraud transactions; including using the Catboost algorithm with undersampling & oversampling methods, and using an almost new approach, by using deep learning and autoencoder.
Credit Card Fraud Detection Using Machine Learning With Python And TensorFlow.
using HMM to detect credit card fraudulent transaction
An implementation of a distributed machine learning algorithm using Spark able to identify fraud in credit card transactions
Deteccion de fraudes de tarjetas de credito usando Machile Learning implementando distintos algoritmos y haciendo comparaciones de rendimiento con respecto a la clasificacion de transacciones.
Credit Card Fraud Detection using Logistic Regression on credit card dataset
A machine learning model to detect fraud in credit card customers using Random Forest Classification Algorithm