hidden layer
A layer in a neural network between the input layer (the features) and the output layer (the prediction).
Plain English Explanation
A layer in a neural network between the input layer (the features) and the output layer (the prediction). Each hidden layer consists of one or more neurons. For example, the following neural network contains two hidden layers, the first with three neurons and the second with two neurons: A deep neural network contains more than one hidden layer. For example, the preceding illustration is a deep neural network because the model contains two hidden layers. See Neural networks: Nodes and hidden layers in Machine Learning Crash Course for more information.
How is it used?
Practitioners refer to hidden layer when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.