February 2019
Beginner to intermediate
308 pages
7h 42m
English
Autoencoders are neural networks that learn a compressed representation of the input, known as the latent representation. They are different from conventional feed forward neural networks because their structure consists of an encoder and a decoder component, which is not present in CNNs.
The size of the latent representation should be sufficiently small enough to represent a compressed representation of the input, and also be sufficiently large enough for the decoder to reconstruct the original image without too much loss.
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