repeated calculation problem

[shm007g]

I've found that you are using sigmoid_prime function in network.py and network2.py to calculate backpropagation. But it is not necessary.

You had calculated activation list in feedforward pass. sigmoid_prime is the derivative of sigmoid function, which is equal to activation * (1 - activation).

You have no need to repeated calculate this sigmoid derivative function, which is really what old-backpropa paper suggest, just one feedforward pass, and a backward pass.

[shm007g]

Do this will get just the same result, may be even better result, for np.exp calculation may have some precision problems.

[MichalDanielDobrzanski]

Closing as this library is just a ported update of neural netwotks Python code