Popular GitHub Repositories for Fraud Detection

Anomaly detection related books, papers, videos, and toolboxes

A Python Library for Graph Outlier Detection (Anomaly Detection)

Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

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

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

Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Code for KDD 2020 paper Robust Spammer Detection by Nash Reinforcement Learning

BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection (WWW23)

MemStream: Memory-Based Streaming Anomaly Detection

Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks

Face recognition SDK iOS with 3D passive liveness detection (Face Detection, Face Landmarks, Face Recognition, Face Liveness, Face Pose, Face Expression, Face attributes)

3D passive face liveness detection, face anti-spoofing, face fraudulent check, face liveness check, face spoof detection, face fraud detection and face analysis on Android.

4 different Big Datasets joined to get single table for final data analysis. Fraud Detection by taken consideration of different key features with applying different Machine Learning Algorithm to see which one performs better.

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

Colab implementation for Fraud Detection in Graph Neural Networks, based on Deep Graph Library (DGL) and PyTorch backend.

The Pytorch Implementation of GCNN model from paper Fake News Detection on Social Media using Geometric Deep Learning