Popular GitHub Repositories for Ad Fraud

A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

Anomaly detection related books, papers, videos, and toolboxes

High-performance automatic differentiation of LLVM and MLIR.

A Python Library for Graph Outlier Detection (Anomaly Detection)

A library created to revitalize C++ as a machine learning front end. Per aspera ad astra.

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

A Deep Graph-based Toolbox for Fraud Detection

哔哩哔哩浏览器插件：基于大语言模型，对B站视频中的植入广告进行检测。一键跳过视频中的植入/口播广告。

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

Awesome graph anomaly detection techniques built based on deep learning frameworks. Collections of commonly used datasets, papers as well as implementations are listed in this github repository. We also invite researchers interested in anomaly detection, graph representation learning, and graph anomaly detection to join this project as contributors and boost further research in this area.

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

An MCP tool that connects Google Ads with Claude AI/Cursor and others, allowing you to analyze your advertising data through natural language conversations. This integration gives you access to campaign information, performance metrics, keyword analytics, and ad management—all through simple chat with Claude, Cursor or Windsurf.

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)

Radient turns many data types (not just text) into vectors for similarity search, RAG, regression analysis, and more.

[CVPR 2023 Workshop] VAND Challenge: 1st Place on Zero-shot AD and 4th Place on Few-shot AD

Repository for the Explainable Deep One-Class Classification paper