To create our network, we will create a class similar to the one we created in the previous chapter for the perceptron. Contrary to what object-oriented programming (OOP) would dictate, we will not take advantage of the perceptron class we previously created, as it's more convenient to work with matrices of weights.
Our goal is to show the code how to understand how to implement the theory we just explained; therefore, our solution will be quite specific for our use case. We know that our network will have three layers, and that the input size will be 2, and we know the number of neurons in the hidden layer:
class FFNN(object):
def __init__(self, input_size=2, hidden_size=2, output_size=1):
# Adding 1 as it will be our bias
self.input_size = input_size + 1
self.hidden_size = hidden_size + 1
self.output_size = output_size...
