AmirhosseinHonardoust/Customer-Churn-Prediction
Customer churn prediction with Python using synthetic datasets. Includes data generation, feature engineering, and training with Logistic Regression, Random Forest, and Gradient Boosting. Improved pipeline applies hyperparameter tuning and threshold optimization to boost recall. Outputs metrics, reports, and charts.
This project helps marketing managers, product managers, and customer success teams identify customers likely to leave your service. You provide historical customer data, including demographics, spending habits, and interaction history. It then generates models, performance reports, and visualizations that highlight key churn drivers and predict who is at risk.
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Use this if you need to proactively identify customers at high risk of churning so you can intervene with targeted retention strategies.
Not ideal if you're looking for a fully-fledged, production-ready SaaS solution for churn prediction without any technical setup or data preparation.
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Language
Python
License
MIT
Category
Last pushed
Sep 11, 2025
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