An input layer is the part of a neural network that receives the feature values or input representation supplied to the model. It passes this information to subsequent layers for transformation and prediction.
The layer of a neural network that holds the feature vector. That is, the input layer provides examples for training or inference. For example, the input layer in the following neural network consists of two features: !Four layers: an input layer, two hidden layers, and an output layer.