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This canvas implements an end-to-end credit risk classification pipeline that loads German credit data, performs exploratory data analysis, trains a Random Forest classifier to predict loan default risk, and evaluates model performance through metrics, feature importance, and ROC curve analysis. The workflow quantifies business impact by calculating cost reduction from using the model versus a baseline approval strategy.