Tejas-00/Customer_Churn_Prediction
Customer Churn Prediction is a machine learning project that identifies customers at risk of leaving a business. It leverages data analytics and predictive modeling to help companies proactively reduce churn, improve retention, and boost growth. The project is built with Python and popular ML libraries for efficient, accurate predictions.
No commits in the last 6 months.
Stars
—
Forks
1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 11, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Tejas-00/Customer_Churn_Prediction"
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...