{"data":{"full_name":"AmirhosseinHonardoust/Fraud-Detection-SQL-Unsupervised","name":"Fraud-Detection-SQL-Unsupervised","description":"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.","stars":30.0,"forks":2.0,"language":"Python","license":"MIT","archived":0.0,"subcategory":"fraud-detection-ml","last_pushed_at":"2025-10-21T12:50:17+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":6.0,"adoption_score":7.0,"maturity_score":13.0,"community_score":6.0,"quality_score":32.0,"quality_tier":"emerging","risk_flags":"['no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-12T13:12:02.938176+00:00"}}