Suggestion on Changing Induction Step for Backward Propagation

I felt an induction step on Z looks simpler than an induction step on A…
Here is a summary.


back prop induction:
dZ(l-1)=w(l)dZ(l) * g’(Z(l-1)) [stores j-derivatives columnwise, each example is 1 column]
dw(l-1)=A(l-2)dZ(l-1)’/m [J-derivative]
db(l-1)=sum(dZ(l-1) over columns)/m [J-derivative]

Though, I dont know much about the literature and any specific advantages the original representation may provide. Look forward to your views.

If you wait until Prof Ng gets to the fully general treatment of all this in Course 1 Week 4, I think that’s the way he does it. It looks like you’re just addressing the Logistic Regression version here.