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Fraud-Detection-SQL-Unsupervised

Detect suspicious financial transactions using SQL and Python. Build user-level behavioral features in SQLite, apply Isolation Forest for anomaly detection, and visualize high-risk patterns. Demonstrates unsupervised fraud analytics and SQL-driven data science workflow.

anomaly-detection banking-data data-analysis data-science financial-analytics fraud-detection isolation-forest machine-learning portfolio-project python

Creat：2025-10-21T20:42:22

Update：2025-10-23T06:11:53

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