A typical neural network has anything from a few dozen to hundreds, thousands or even millions of artificial neurons arranged in a series of layers, each of which connects to the layers on either side. The first layer is the layer in which inputs are entered, which are designed to receive various forms of information from the outside world that the network will attempt to learn about, recognize, or otherwise process. Other neurons sit on the opposite side of the network and signal how it responds to the information it’s learned; this layer is known as the output layer. In between the input and output layers, are one or more layers of hidden units, which, together, form the majority of the artificial brain. These layers are called hidden layers.

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Beathanabhotla, S. (2022, January 21). Text Classification using Neural Networks. Holler Developers. https://medium.com/holler-developers/text-classification-using-neural-networks-400a5a32f88