Telecom-Customer-Churn-Analysis-Prediction and telecom-customer-churn-prediction

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Stars: 6
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Language: Jupyter Notebook
License: MIT
Stars: 20
Forks: 4
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Language: HTML
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About Telecom-Customer-Churn-Analysis-Prediction

VibolvatanakPOCH/Telecom-Customer-Churn-Analysis-Prediction

Telecom Customer Churn Analysis & Prediction project uses Gradient Boosting for precise predictions, Power BI for churn pattern visualizations, and Streamlit for interactive insights. With robust code and meticulous data preprocessing, stakeholders access accurate predictions to optimize retention and drive profitability.

About telecom-customer-churn-prediction

virajbhutada/telecom-customer-churn-prediction

Predict and prevent customer churn in the telecom industry with our advanced analytics and Machine Learning project. Uncover key factors driving churn and gain valuable insights into customer behavior with interactive Power BI visualizations. Empower your decision-making process with data-driven strategies and improve customer retention.

This project helps telecom companies predict which customers are likely to switch to another provider. It takes customer usage patterns, behavior, and other service-related data as input and provides a list of at-risk customers along with insights into why they might leave. This is ideal for customer retention managers, marketing strategists, and business analysts in the telecom sector.

telecom-customer-retention churn-prediction customer-behavior-analysis telecom-marketing customer-segmentation

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