Tool-Wear-And-Fault-Prediction-System JayasaiKarthik-G · PARTIAL
Machine learning-based tool wear and fault prediction system using Random Forest, Scikit-learn, and Streamlit for real-time predictive maintenance.
github.com/JayasaiKarthik-G/Tool-Wear-And-Fault-Prediction-System · ★ 0 · Forks 0 · Size 2.1 MB
SUMMARY
Technologies 5
Scored 4
Observed 4
Practices 6
Evidence 6
Skips 1
COVERAGE
Analyzed 9 files · 3 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
2 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth —
0 files · config only
pandas LIBRARY Depth 58
2 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2026-07-26
Last commit 2026-07-26
Active months 1
Commits 3