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scaler.fit_transform(df[['column']]) Z-Score Normalization (Standardization): Data is transformed to have a mean of 0 and a standard deviation of 1. It’s especially useful for algorithms that rely on distances or gradients. from sklearn.preprocessing import StandardScaler scaler = StandardScaler()