why do we actually need to normalize the data (i.e. make it’s mean=0 and std=1 ), before we write the functions and predict the value for test data?
Normalizing the data
Standardizing is important when we compare measurements that have different units. Variables that are measured at different scales do not contribute equally to the analysis and might end up creating a bias.
For example, A variable that ranges between 0 and 1000 will outweigh a variable that ranges between 0 and 1. Using these variables without standardization will give the variable with the larger range weight of 1000 in the analysis. Transforming the data to comparable scales can prevent this problem.
Another advantage is reduced training time. Models which are trained on scaled data converge faster compared to untouched data.
Hope this helps!
Thank you sir
That helped!! 
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Glad I could help you!