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Explain the difference between a shallow network and a deep network.

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A hidden layer, as well as input and output layers, are present in every neural network. Shallow neural networks are those that have only one hidden layer, whereas deep neural networks include numerous hidden layers. Both shallow and deep networks can fit into any function, however, shallow networks require a large number of input parameters, whereas deep networks, because of their several layers, can fit functions with a small number of input parameters. Deep networks are currently favored over shallow networks because the model learns a new and abstract representation of the input at each layer. In comparison to shallow networks, they are also far more efficient in terms of the number of parameters and computations.

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