Feedforward networks approximate functions

In supervised learning, simple perceptrons have been shown to be able to accurately describe an extremely broad family of functions. However, they would need an extremely wide single layer to do this, sometimes even larger than there are atoms in the universe, making it unfeasible to train. In light of this deep learning is more economical.

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