Feedforward Neural Network

A feedforward neural network is a type of computer model that mimics how the human brain processes information. It consists of layers of interconnected nodes or "neurons," where data flows in one direction from the input layer (receiving information) to hidden layers (processing and extracting features), and finally to the output layer (producing a result). Each connection has a weight that adjusts based on learning, helping the network improve its accuracy over time. This structure is commonly used for tasks like recognizing images, translating languages, and predicting outcomes.