Popular GitHub Repositories for Crypto Fraud

Investment Research for Everyone, Everywhere.

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

Anomaly detection related books, papers, videos, and toolboxes

ValueCell is a community-driven, multi-agent platform for financial applications.

Algorithmic Trading in Python with Machine Learning

Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

DATAGEN: AI-driven multi-agent research assistant automating hypothesis generation, data analysis, and report writing. Now expanding into crypto market intelligence. Learn more: https://datagen.digital/.

IBM Fully Homomorphic Encryption Toolkit For Linux. This toolkit is a Linux based Docker container that demonstrates computing on encrypted data without decrypting it! The toolkit ships with two demos including a fully encrypted Machine Learning inference with a Neural Network and a Privacy-Preserving key-value search.

A Python Library for Graph Outlier Detection (Anomaly Detection)

The open-source framework for connecting AI agents to any onchain app

Train and Deploy an ML REST API to predict crypto prices, in 10 steps

A Deep Graph-based Toolbox for Fraud Detection

Free self-hosted market-making bot for crypto projects & token issuers. Volume, spread, liquidity, price ranges, and dynamic order books — all in one.

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

The AutoGPT MetaTrader Plugin is a software tool that enables traders to connect their MetaTrader 4 or 5 trading account to Auto-GPT.

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

AI-Hedge-Fund for Crypto ? AI-powered hedge fund for cryptocurrency trading, leveraging LLM agents for intelligent decision-making.

OK | Every voice, every meme, every transaction makes $OK stronger and more vibrant. Powered by all of us—and now, AI agents. OK is not just OK — it’s $OK. $OK?

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.