Hand computing feed forward and back propagation of neural network I used to treat back propagation as a black box but lately I want to understand more about it. I have used mattmuzr's and DuttA's explanaiton as a guide to hand compute a simple neural network. I have computed feed forward and back propagation to a network similar to this one with one input, one hidden and one output



Here are my computations







Is my computations correct?

*Full latex code
One important point I missed in first review: error is a summatory, its derivative is also a summatory.

About offsets "b": usually they are different in each cell (if not fixed to some value, as 0). Thus, replace them by b1 and b2. Moreover, they should be optimized in the same way that the weights.