This helped me a lot in understanding the math behind gradient descent pretty well. The only problem I faced was when I tried to derive the equations for a vect

This helped me a lot in understanding the math behind gradient descent pretty well. The only problem I faced was when I tried to derive the equations for a vectorised implementation of a neural network. Certain derivatives, like the derivatives of matrix multiplication, are not obvious from the from the math presented in the paper. Had to dig through a bit to bridge that gap between non vectorised and vectorised implementations. By vectorised implementation of gradient descent, I mean one where gradient descent looks at more that one training samplenat a time when updating weights