{"blocks": [{"key": "cd653132", "text": "Scenario", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "5b6e6f84", "text": "BCG CodeSignal notebook – feature scaling step before modeling", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "a9094330", "text": "Question", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "5625dee6", "text": "Given a DataFrame df with numeric columns age and income, demonstrate how to Standard-scale age and Min-Max normalize income. Explain when you would prefer each scaler.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "6a177c3c", "text": "Hints", "type": "header-two", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}, {"key": "fab00499", "text": "Use sklearn.preprocessing; relate to Gaussian vs bounded distributions.", "type": "unstyled", "depth": 0, "inlineStyleRanges": [], "entityRanges": [], "data": {}}], "entityMap": {}}