{"repo":"ashishallu/fraud-detection-pipeline","free":true,"listed":false,"github":"https://github.com/ashishallu/fraud-detection-pipeline","clone":"git clone https://github.com/ashishallu/fraud-detection-pipeline.git","description":"Real-time financial fraud detection pipeline using Kafka, Spark Streaming, machine learning, and Docker to identify suspicious transactions with low-latency processing and live monitoring.","language":"Python","stars":11,"topics":["docker","geometric","graphical-neural-networks","kafka","pyspark","pytorch","shap","streamlit-dashboard"],"license":null,"category":"machine-learning","readme_excerpt":"🔍 Real-Time Fraud Detection Pipeline Kafka → Spark Structured Streaming → Graph Neural Network → Gradient-Attribution Explainability A production-style, end-to-end real-time fraud detection system. Streams live transactions through a heterogeneous Graph Neural Network (HeteroGraphSAGE) trained on the IEEE-CIS dataset, with per-decision gradient-attribution explainability and a live Streamlit dashboard. --- Architecture --- Model Performance Metric Score --- --- AUC-ROC 0.796 Precision 0.211 Recall 0.987 F1 Score 0.347 Evaluated on a temporal (chronological) test split — see MODEL CARD.md for the full methodology, an honest before/after comparison against the original (leakier) evaluation, why precision looks lower here than an earlier version of this table claimed, and how the decision threshold was chosen. Trained on a 110,663-row sample (all 20,663 fraud rows + 90,000 randomly sampled legitimate rows) from the IEEE-CIS Fraud Detection dataset (590,540 rows total) — not the full dataset. See MODEL CARD.md for why, and what that means for transactions on cards/merchants outside the sample. --- Dashboard Preview Page What it shows --- --- Live Monitor Real-time fraud rate, transaction feed, auto-refreshes every 3s Fraud Investigation Gradient-attribution explanations + graph connections for any flagged transaction Model Performance Training curves, confusion matrix, feature importance Graph Explorer Subgraph visualization for any card ID See fraud-detection-pipeline-demo.mp4 ","default_branch":null,"files":null,"tree":[],"storefront":"/r/ashishallu","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ashishallu/fraud-detection-pipeline/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}