Feedforward Neural Network

In feedforward neural networks, information moves from the input layer to the output layer without forming cycles. This structure provides the foundational framework for parameter learning in classical supervised tasks. Many later deep learning architectures can be understood as specialized adaptations of this basic flow. While conceptually simple, its expressive power can grow substantially with added depth and neuron capacity.