Hidden Layer
Hidden layers are vital in neural networks, processing inputs through transformations that enable learning of complex data patterns.
A hidden layer is a component of a neural network that sits between the input layer and the output layer. It consists of neurons that apply transformations to the input data through weights and activation functions. Hidden layers are essential for enabling the network to learn complex patterns and representations from the data.