print('[0, 1] -> {}'.format(nn.activate([0, 1])))
print('[1, 0] -> {}'.format(nn.activate([1, 0])))
print('[1, 1] -> {}'.format(nn.activate([1, 1])))
print()
# 4.3 B. Delta Rule
# Neural Network Settings
learning_rate = 100
epochs = 1000
weight_lower_bound = -1
weight_upper_bound = 1
rng = np.random.RandomState(seed=None)
nn = NeuralNetwork(3, [], [NeuronInfo(sigmoid, sigmoid_derivative)])
print('Training a NOR Gate:\n{}\n'.format(nn))
nn.randomize(rng, weight_lower_bound, weight_upper_bound)
print('Training...')
inputs = np.array([
[0, 0, 0],
[0, 0, 1],
[0, 1, 0],
[0, 1, 1],
[1, 0, 0],
[1, 0, 1],
[1, 1, 0],
[1, 1, 1],
])
expected_outputs = np.array([
[1],
[0],
