[Screenshot 2024-10-13 at 11.53.37 PM] Where did these derivations come from? From last week lectures, the following was concluded regarding derivation of dZ, dA dZ = dL/dZ = A - Y dA = dL/dA[2] = -Y/A + (1-Y)/(1-A) Moreover, there’s no mention of the loss function L.

Didn't get the derivation

paulinpaloalto October 14, 2024, 2:03am 4

Here’s a thread from Mubsi and Eddy that covers those derivations.

Topic		Replies	Views
BackPropagation Derivation Of 2 Layer Neural Network Neural Networks and Deep Learning week-module-3 , coursera-platform	1	251	March 3, 2024
Could someone help explain about this to me? Neural Networks and Deep Learning coursera-platform	1	624	May 24, 2023
Backprop derivative after output later - Course 1: Week 3 Neural Networks and Deep Learning coursera-platform	4	614	June 22, 2024
Derivation of dz=da* g'(z) ? or dz= a- y? how is derivation of dz[1] and dz[2] different? Neural Networks and Deep Learning coursera-platform	10	978	June 1, 2023
Back propagation why do we start from dZ2 and why transpose Neural Networks and Deep Learning week-module-3 , coursera-platform	2	338	May 30, 2024