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
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 pipeline detecting product fraud and IP infringement in marketplace listings. Built in public in 21 days
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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