AI-Productivity-Tracker AmirhosseinHonardoust · COMPLETED
Analyze and predict daily productivity using SQL, machine learning, and psychology. This project combines behavioral data, circadian rhythm analysis, and ElasticNet regression to model focus, stress, and performance, transforming work patterns into actionable insights.
github.com/AmirhosseinHonardoust/AI-Productivity-Tracker · ★ 34 · Forks 0 · Size 689 KB
SUMMARY
Technologies 11
Scored 11
Observed 11
Practices 6
Evidence 13
Skips 0
COVERAGE
Analyzed 32 files · 42 commits · 0 API calls
TECHNOLOGIES & DEPTH
JSON LANGUAGE Depth 70
1 files · PRODUCTION
TOML LANGUAGE Depth 70
1 files · PRODUCTION
Markdown LANGUAGE Depth 70
3 files · PRODUCTION
YAML LANGUAGE Depth 70
2 files · PRODUCTION
Python LANGUAGE Depth 70
14 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 66
3 files · PRODUCTION
pandas LIBRARY Depth 78
11 files · PRODUCTION, TEST
pytest TESTING Depth 45
3 files · TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · observedcontainerization · absentlinting · observedformatting · observed
ACTIVITY & OWNERSHIP
First commit 2025-10-24
Last commit 2026-09-09
Active months 2
Commits 42