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customerretention

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The "Churn Prediction" project analyzes customer data to identify factors leading to churn 📉🤔. Using machine learning algorithms, it predicts which customers are likely to leave, enabling businesses to implement targeted retention strategies and improve customer satisfaction.

  • Updated Jun 26, 2021
  • Jupyter Notebook

This project develops a machine learning model to predict customer churn for a California-based telecom company using data from 7043 customers. Our goal is to enhance customer retention strategies through detailed data analysis and feature engineering.

  • Updated May 9, 2024
  • Jupyter Notebook

End-to-End Retail Customer Churn Prediction using Gradient Boosting and Streamlit. This repository showcases a comprehensive data science workflow, from feature engineering with RFM to building a Gradient Boosting model and deploying an interactive dashboard for actionable customer retention insights.

  • Updated Jun 21, 2025
  • Jupyter Notebook

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