do we always need to normalize our data ? or is it just for when we process Logistic Regression ?

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do we always need to normalize our data ? or is it just for when we process Logistic Regression ?

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i don't understand this part below

# split features from target variable

trainLabel = np.asarray(dfTrain['Outcome'])trainData = np.asarray(dfTrain.drop('Outcome',1))testLabel = np.asarray(dfTest['Outcome'])testData = np.asarray(dfTest.drop('Outcome',1))

why do we need to do this ?

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