Multilayer Perceptron

A multilayer perceptron (MLP) is a type of artificial neural network used in machine learning to solve complex problems like recognizing images or understanding language. It consists of layers of interconnected nodes, or "neurons." The input layer receives data, which is processed through one or more hidden layers that analyze patterns, and then produces an output, like a prediction or decision. Each connection has a weight, helping the network learn from data by adjusting these weights during training. Overall, an MLP learns to make accurate decisions by mimicking how brain neurons process information.