Im new to Machine Learning , so please just dont blast me .

Im studing the Gradient Descent single layer algorithm.
Suppose that i have an initial dataset and then i use the Mean Normalization in order to scale the features.

Why mathematically do the normalizated features carry the same information of the initial features ?