Perceptron and Multi-layer Perceptrons

A perceptron is a fundamental building block of neural networks, acting as a single-layer linear classifier. It takes several inputs, multiplies each by a weight, sums them up, and then applies an activation function to produce an output. Multi-layer perceptrons (MLPs) extend this concept by stacking multiple layers of perceptrons, including an input layer, one or more hidden layers, and an output layer, allowing for the modeling of more complex, non-linear relationships in data.