gradient calc description change

I have found the previous explanation of manual gradient calculation a
little confusing because we compute a vector of gradients with the size
of number of neurons (with bias) and in the explanation it looks like we
compute a scalar.

Propose more detailed variant if community finds it's better. Excuse me
if  it is convenient to write x_i even for bias unit, just discard this
then.