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This canvas contains a single Python block that builds a complete AI-driven churn prediction and revenue retention optimization system, engineering RFM features from e-commerce data, training a Gradient Boosting classifier to predict customer churn, and identifying high-risk customers with revenue-optimized decision thresholds for targeted retention campaigns. The system includes an deployable API function for real-time churn probability scoring and revenue risk assessment.