Calculus for Deep Learning, with Vectors, Matrices, and a few Tuples

This note derives the gradients for training a deep neural network while trying to use only matrix algebra and vector calculus. It isn’t quite enough so we have to add a little more structure based on ‘tuples’, basically a list of stuff, which can be utilized intuitively.

Link:  Calculus for Deep Learning, with Vectors, Matrices, and a few Tuples