Credit-Risk-Prediction-with-Logistic-Regression Muzammil592 · COMPLETED
Can we predict which borrowers will default on a loan? I built logistic regression from scratch in NumPy, checked it against scikit-learn, and tuned it to catch risky loans. Includes data cleaning, clear charts, and a simple Streamlit app where you can try it yourself.
github.com/Muzammil592/Credit-Risk-Prediction-with-Logistic-Regression · ★ 1 · Forks 0 · Size 42 KB
SUMMARY
Technologies 5
Scored 5
Observed 5
Practices 6
Evidence 6
Skips 0
COVERAGE
Analyzed 13 files · 4 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
9 files · PRODUCTION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
NumPy LIBRARY Depth 78
9 files · PRODUCTION
pandas LIBRARY Depth 78
5 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2026-10-06
Last commit 2026-10-11
Active months 1
Commits 4