Modern & flexible browser fingerprinting library

Modern Web Firewall: stop account takeovers, weak passwords, cloud IPs, DoS attacks, disposable emails

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.

💰 Billing & Payments Knowledge for Cloud Platforms

Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in this scenario? Find the answers in this code pattern!

🚨 Hoaxwagen detects Volkswagen in dependencies to prevent tests fraud

Case Studies on Forensic Accounting using Data Analysis

Classification of fraudulent credit card transactions.

Protect online forms from spam by making them perform Proof of Work (PoW).

Ten Simples Rules for Scientific Fraud and Misconduct

An online directory to list spammers, frauds or scammers. Search spammers by keywords. Report spammers in spamsort and share them to the world!

MyAdmin MaxMind Fraud Plugin

MyAdmin FraudRecord Fraud Plugin

Music and text generation with Transformer-XL.

Fraud Detection in Transactions analysis using Deep Learning and exploiting Deep Transfer Learning technique for it.

[PROGRESSING] Warning: The project pends big reformation. We are on work of this. This document is not making sense here.

Implementation of an intelligence system to detect the fraud cases on the basis of classification.

A fraud analysis tool used to check for invalid and disposable email domains.

This project is from Kaggle - Credit Card Fraud Detection

Card-Not-Present Fraud Project: in an imbalanced dataset containing 200,000 financial transactions, I was asked with identifying 400 rows of fraud. This Random Forest model successfully caught about 75% true positives, with only 0.00025% false positives.

using HMM to detect credit card fraudulent transaction

The Credit Card Fraud Detection Problem includes modeling past credit card transactions with the knowledge of the ones that turned out to be fraud. This model is then used to identify whether a new transaction is fraudulent or not.

Credit Card Fraud Analysis and Detection - - Anonymized credit card transactions labeled as fraudulent or genuine. The project was intended to detect fraudulent transactions from a highly imbalanced dataset.

Library for working with the pseudo-cryptocurrency PRIZM. Designed specifically for unlucky developers forced to face this sh*t

This repository contains the overview of all the approaches that we are applying in order to detect Fraud

Classifying Credit Card transactions as fraudulent or genuine using Classification techniques.

Fraud Case Study

This project intends to solve the house hunt problem by sending the updates of new listings as per the selection criteria of the user by filtering spam in housing listings using NLP. It uses SMTP to send emails, nltk for NLP and tkinter for creating UI

Morphological demonstration that Trump is a fraud

Fraud Detection using ensemble of Statistical, Network analysis and Machine learning approach.