question42.py

'''
Long version of simple neural network

https://medium.com/technology-invention-and-more/how-to-build-a-simple-neural-network-in-9-lines-of-python-code-cc8f23647ca1
'''

# not working

from numpy import exp, dot, array, random


class NeuralNetwork():
    def __init__(self):
        random.seed(1)
        self.synaptic_weights = 2 * random.random((3, 1)) - 1

    def __sigmoid(self, x):
        return 1 / (1 + exp(-x))

    def __sigmoid_derivative(self, x):
        return x * (1 - x)

    def train(self, training_set_inputs, training_set_outputs, number_of_training_iterations):
        for iteration in number_of_training_iterations:
            output = self.think(training_set_inputs)
            error = training_set_inputs - output

            adjustments = dot(training_set_inputs.T, error * self.__sigmoid_derivative(output))

            self.synaptic_weights += adjustments

    def think(self, inputs):
        return self.__sigmoid(dot(inputs, self.synaptic_weights))


if __name__ == "__main__":
    neural_network = NeuralNetwork()
    print("Random starting synaptic weights : ")
    print(neural_network.synaptic_weights)

    training_set_inputs = array([[0, 0, 1], [1, 1, 1], [1, 0, 1], [0, 1, 1]])
    training_set_outputs = array([[0, 1, 1, 0]]).T
    number_of_training_iterations = 10000

    neural_network.train(training_set_inputs, training_set_outputs, number_of_training_iterations)

    print("New synaptic weights after training: ")
    print(neural_network.synaptic_weights)

    print("Considering new situation [1, 0, 0] -> ?: ")
    print(neural_network.think(array([1, 0, 0])))