{"blocks": [{"key": "f632e03f", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "4b692a7d", "text": "Building a churn-prediction pipeline for a subscription business using scikit-learn.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "c1de1310", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "0b42caea", "text": "Describe, step-by-step, how you would construct, train, validate, and evaluate a churn-prediction model in scikit-learn, including preprocessing, model choice, hyper-parameter tuning, and packaging the final pipeline for production.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "981c1f00", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "052bd723", "text": "Mention Pipeline, ColumnTransformer, GridSearchCV, cross-validation, joblib.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}