In regression, do i need uniform distribution of output?

I'm working on above example and there is some saying i don't understand. First, in "Check Data Normalization", there is saying that "the response (the rotation angle in degrees) is approximately uniformly distributed between -45 and 45, which works well without needing normalization". I understand why i need normalization but i don't understand unform distribution of output(=response) works weel without needing normalization.   And second, there is also saying that "If the distribution of the input or response is very uneven or skewed, you can also perform nonlinear transformations (for example, taking logarithms) to the data before training the network". Here, i don't understand why uneven and skewed distribution are not going to work well.