Perceptrons

A perceptron is a basic building block of artificial neural networks, designed to classify data. It takes multiple input signals, each weighted to reflect their importance, sums them up, and then applies a rule (activation function) to decide on an output, typically yes or no. Think of it like a simple decision-maker: if the weighted inputs reach a certain threshold, it says "yes"; otherwise, "no." Perceptrons can learn by adjusting these weights based on experience, enabling them to improve decision accuracy over time. They serve as the foundation for more complex patterns in machine learning.