# Guided Project: Predicting Car Prices_normalizing_data

I was doing the guided project for Predicting Car Prices (Introduction to Machine Learning)

while normalizing the date i see in the solution below method is used

numeric_cars = (numeric_cars - numeric_cars.min())/(numeric_cars.max() - numeric_cars.min())

while during practice we have used

numeric_cars = (numeric_cars -numeric_cars.mean())/numeric_cars.std()

so why it is different and what is the approach for normalizing data.

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The approach for normalizing data depends on the distribution of the data and what are you trying to achieve.