A perceptron is the basic part of a neural network.
A perceptron represents a single neuron on a human’s brain, it is composed of the dataset ( Xm ) , the weights ( Wm ) and an activation function, that will then produce an output and a bias.
The datasets ( inputs ) are converted into an ndarray which is then matrix multiplied to another ndarray that holds the weights.
Summing up all matrix multipy and adding a bias will create the net input function, the output would then passed into an activation function that would determine if the neuron needs to fire an output or not.
Most common activation function used for classification used is a sigmoid function, which is a great function for classification .
Assignment : Gates to implement
Find the weights and bias for the other gates.