A topic that I found a bit confusing was the distinction between channels vs number of filters that can be used to create stackable convolution outputs. In the lecture, Andrew used notation Nc and Nc’ to distinguish between channels and # of filters. However, this took me a but to understand the difference especially when you consider that channels are convoluted together from the previous layer whereas each filter is used independently to create stacked dimensions.
Where I got really stuck was in the 1st assignment for Week 1, for conv_forward function where it says “loop over channels (= #filters) of the output volume” -I found this is misleading as there is a distinction between channels and # of stacked filters. The iteration is over one of these, while the other is used in the convolution step. So I felt there was a bit of a disconnect between lecture and this assignment in clarifying that we are dealing with 4 dimensions and not 3 as the lecture suggests- and that we hold one dimension constant while fully convoluting over the other.
Figured I’d post in case people were running into similar confusion.