mahmoudbalal784-create/Logistic-Regression

📊 Build a Logistic Regression model to predict customer churn in telecom, utilizing Python and scikit-learn for data analysis and insights.

/ 100

Experimental

No Package No Dependents

Maintenance 13 / 25

Adoption 0 / 25

Maturity 9 / 25

Community 0 / 25

Stars

—

Forks

—

Language

Jupyter Notebook

License

Apache-2.0

Category

Last pushed

Mar 19, 2026

Commits (30d)

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mahmoudbalal784-create/Logistic-Regression"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

retentioneering/retentioneering-tools

Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web...

iterative/demo-bank-customer-churn

Demo DVC project training a classification model on tabular data

junfengn-ctrl/uplift-modeling-customer-retention

End-to-end uplift modeling pipeline for customer retention using T-Learner and X-Learner with...

Pradnya1208/Telecom-Customer-Churn-prediction

Customers in the telecom industry can choose from a variety of service providers and actively...

gattsu001/Telecom-Churn-Predictor

Predicts which telecom customers are likely to churn with 95% accuracy using engineered features...