In my textbook, I read that whenever you reduce the mean of each feature from corresponding features in the training data and divide each feature by its standard deviation (this process is called Normalizing input data), the bias term is not significant. I don't understand this. Why is that?
To provide extra clarification I provided the following image:
(The left one is badly conditioned and the right one is the one which has been normalized).