Sir said that it makes convergence faster and better visualisation of data.But why convergence becomes faster in after we normalise?
Why do we do normalisation of data?
Hey @nikhil_sarda, consider a data set containing two features, age, and income(x2). Where age ranges from 0–100, while income ranges from 0–100,000 and higher. Income is about 1,000 times larger than age. So, these two features are in very different ranges. When we do further analysis, like multivariate linear regression, for example, the attributed income will intrinsically influence the result more due to its larger value. But this doesn’t necessarily mean it is more important as a predictor. So we normalize the data to bring all the variables to the same range.
The above was the prime reason to normalize the data, Now second reason is that normalization makes convergence faster, because when you will calculate gradients, in this example, as you are already aware of the formula it contains x in multiplication, so you can imagine the gradients, will be quite large, and we do not tend to make such long jumps, so to compensate this we have to reduce learning rate by 1000/10000 etc, so now you can imagine how slow will be the convergence.
Hope this resolved your doubt.
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