I was really looking forward to an explanation for how a neural network is trained via back-propagation, but we really only covered which functions to call in Tensorflow. Is there an article//video someone could recommend that covers an explanation for what is actually happening during back-propagation? It’s odd to me that this wasn’t really covered since it’s a critical detail in understanding a neural network.
I personally like this article here:
Yeah exactly! Why was this ignored completely? We should have had at least an Optional section providing an intuitive understanding of how back propagation works.
Hope a mentor can explain the rationale for skipping this topic entirely.
I think there should be some ongoing effort about back propagation. Please check this message by a member of the course team, and there you can find a link to another thread which has some relevant materials.
Thank you @rmwkwok! I found that thread after commenting here. Looking forward to the upcoming video!
You are welcome @Prax!