Credit-CardFraudDetection

Anomaly detection related books, papers, videos, and toolboxes

Synthetic data generators for tabular and time-series data

A Python Library for Graph Outlier Detection (Anomaly Detection)

Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

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

Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022

Generate relevant synthetic data quickly for your projects. The Databricks Labs synthetic data generator (aka `dbldatagen`) may be used to generate large simulated / synthetic data sets for test, POCs, and other uses in Databricks environments including in Delta Live Tables pipelines

Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters