import random

nn = NeuralNetwork(2,2,1)
inputs  = np.array([[0, 0], [1, 0], [0, 1], [1, 1]])
targets = np.array([[0], [1], [1], [0]])
zipped = zip(inputs, targets)
list_zipped = list(zipped)

for _ in range(9000):
    x, y = random.choice(list_zipped)
    nn.train(x, y)

output = [nn.feedforward(i) for i in inputs]

for i in output:
   print("Output ", i)

#Output  [ 0.1229546]  when it should be around 0
#Output  [ 0.6519492]  ~1
#Output  [ 0.65180228] ~1
#Output  [ 0.66269853] ~0

[ 0.93749991] # should be ~1
[ 0.93314793] # ~1
[ 0.07001175] # ~0
[ 0.06576194] # ~0