An end-to-end Machine Learning project for credit card fraud detection, covering data analysis, preprocessing, model training, evaluation, and deployment.
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Updated
Jul 21, 2026 - Jupyter Notebook
An end-to-end Machine Learning project for credit card fraud detection, covering data analysis, preprocessing, model training, evaluation, and deployment.
ML-powered fake job detector — Linear SVM + DistilBERT ONNX, 10-signal URL scorer, runtime model switching.
📝 Logistic regression fraud classifier on 284K+ transactions — 87% accuracy, 94% AUC-ROC
End to end pipeline detecting product fraud and IP infringement in marketplace listings. Built in public in 21 days
A SIEM-based Fintech Threat Monitoring project using Splunk Enterprise to investigate suspicious transactions, phishing indicators, transaction structuring, malicious IP activity and threat hunting through interactive dashboards and SPL queries
End-to-end ML platform for credit risk & fraud detection: 9 models (incl. TabNet), SHAP/LIME explainability, MLflow tracking, FastAPI serving, Docker deployment. 96% test coverage.
AI-powered scam detection platform built with Reflex, Python, Supabase, Groq AI, Docker, and Railway. Detect fraudulent messages, URLs, QR codes, and screenshots in real time.
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