Multi-layer perceptrons

A Multi-layer Perceptron (MLP) is a type of artificial neural network used for tasks like recognizing images or understanding speech. It consists of layers of interconnected nodes (or "neurons"). The input layer takes in data, like pixels from an image. Hidden layers process this information, transforming it through mathematical functions to find patterns. The final output layer produces a result, such as identifying objects. The network "learns" by adjusting connections based on errors, improving its accuracy over time. Essentially, MLPs are structured to mimic how brains process information, enabling computers to learn from data.