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fraud-detection

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An end-to-end blueprint architecture for real-time fraud detection(leveraging graph database Amazon Neptune) using Amazon SageMaker and Deep Graph Library (DGL) to construct a heterogeneous graph from tabular data and train a Graph Neural Network(GNN) model to detect fraudulent transactions in the IEEE-CIS dataset.

  • Updated Mar 31, 2024
  • TypeScript

Save From Frauds is a comprehensive application designed to track and report fraudulent entities (e.g., phone numbers, emails, websites) and their associated impacts. Users can log detailed reports describing the nature of the fraud, its impact (financial, emotional, reputational, etc.), and preventive measures to avoid similar scams.

  • Updated Apr 12, 2025
  • TypeScript

The Segment Source function allows you to use Fingerprint Pro visitor identification data as a data source in Segment. The function recieves the data through webhooks and normalizes them into Segment Specs.

  • Updated Nov 8, 2024
  • TypeScript
Fraud-Detector---E-commerce-Platform-Tool

A Flask-based fraud detection dashboard that analyzes e-commerce transactions in real-time using machine learning (Scikit-Learn), flags suspicious activity via WebSockets, visualizes trends with Chart.js, and stores data in SQLite - showcasing full-stack Python skills with a focus on AI/ML integration and real-time analytics

  • Updated Jun 29, 2025
  • TypeScript

TradeSpace is an online platform that aims to provide a convenient and user-friendly way for individuals to sell their used products. The platform will serve as a marketplace where sellers can list their items and connect with potential buyers who are interested in purchasing pre-owned goods.

  • Updated Sep 18, 2023
  • TypeScript

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