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This canvas implements a comprehensive customer churn prediction and risk segmentation platform that combines data cleaning, feature engineering, machine learning model training, and multi-faceted visualization. The workflow extracts telco customer data, creates RFM-style behavioral features, trains a Gradient Boosting classifier to predict churn probability, and generates an actionable dashboard with high-risk customer segmentation, model performance visualizations, and detailed insights on service adoption, geographic distribution, and revenue at risk—enabling targeted retention strategies across 7,043 total customers with 972 flagged as high-risk (≥65% churn probability).