# Why do we normalize data in a deep neural network?

I have asked this question a number of times, but I always get confusing answers to this, like "normalized data works better", "data lives in the same scale"

How can x-m/s make the scale of images the same? Please explain to me the maths. Also, take MNIST dataset for example & illustration.