From Perceptron to Neuron

A perceptron is a mathematical model of a biological neuron that takes numerical inputs, applies weights, adds a bias, and uses an activation function to produce a binary output, classifying data into two categories.

The original perceptron computed: y = step(w·x + b). Modern neurons do: z = w·x + b, then a = φ(z) where φ is an activation function (e.g., ReLU, sigmoid, tanh). Stacking many neurons gives you a layer; stacking layers gives you a network.