malhotrachetan / artificial-intelligence-recipes Goto Github PK

#backpropogation of errors
l2_error = y-2
if(i % 10000): #print the error every 10000 steps to save time and to limit the amount of output
    print("Error: " + str(np.mean(np.abs(l2_error))))
    
l2_delta = l2_error*sigmoid(l2,deriv=True)
l1_error = l2_delta.dot(syn1.T)
l1_delta = l1_error * sigmoid(l1,deriv=True)

#updating weights
syn1 += l1.T.dot(l2_delta)
syn0 += l0.T.dot(l1_delta)