Fraud-Detection-SQL-Unsupervised AmirhosseinHonardoust · PARTIAL
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.
github.com/AmirhosseinHonardoust/Fraud-Detection-SQL-Unsupervised · ★ 28 · Forks 3 · Size 3.3 MB
SUMMARY
Technologies 10
Scored 9
Observed 9
Practices 6
Evidence 12
Skips 1
COVERAGE
Analyzed 19 files · 21 commits · 0 API calls
TECHNOLOGIES & DEPTH
TOML LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
2 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
7 files · PRODUCTION
SQL LANGUAGE Depth 70
1 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
Poetry BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth —
0 files · config only
pandas LIBRARY Depth 78
5 files · PRODUCTION, TEST
pytest TESTING Depth 37
1 files · TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2025-10-21
Last commit 2026-09-06
Active months 2
Commits 21