AI-Assistant-Satisfaction-Prediction-Engine AmirhosseinHonardoust · PARTIAL
A complete machine-learning system that predicts AI assistant user satisfaction using behavioral signals such as device, usage category, time features, session metrics, and model metadata. Includes full ML pipeline, SHAP explainability, evaluation suite, and an interactive Streamlit analytics dashboard.
github.com/AmirhosseinHonardoust/AI-Assistant-Satisfaction-Prediction-Engine · ★ 18 · Forks 0 · Size 3.4 MB
SUMMARY
Technologies 13
Scored 10
Observed 10
Practices 6
Evidence 15
Skips 3
COVERAGE
Analyzed 37 files · 12 commits · 0 API calls
TECHNOLOGIES & DEPTH
JSON LANGUAGE Depth 70
3 files · PRODUCTION
TOML LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
YAML LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
22 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
Poetry BUILD_TOOL Depth 80
1 files · CONFIGURATION
Black QUALITY Depth —
0 files · config only
NumPy LIBRARY Depth 78
9 files · PRODUCTION, TEST
Ruff QUALITY Depth —
0 files · config only
mypy QUALITY Depth —
0 files · config only
pandas LIBRARY Depth 78
10 files · PRODUCTION, TEST
pytest TESTING Depth 22
1 files · TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · absent
ACTIVITY & OWNERSHIP
First commit 2025-12-05
Last commit 2026-07-04
Active months 2
Commits 12