This implementation is for multiple feature?

We have just consider X[i] while calculating the gradient function
what about other features

Hey @ysh, it seems your are getting little bit confused. X is of shape (m,n) where m is no of training examples, and n is no of features. So by specifying X[i] we are using the m th example, so it will contain all n features of mth example in it.

Hope this cleared your doubt. :blush:

got it now , Didn’t notice that