December 2019
Intermediate to advanced
468 pages
14h 28m
English
To understand VAEs, we need to talk about regular autoencoders. An autoencoder is a feed-forward neural network that tries to reproduce its input. In other words, the target value (label) of an autoencoder is equal to the input data, yi = xi, where i is the sample index. We can formally say that it tries to learn an identity function,
(a function that repeats its input). Since our labels are just input data, the autoencoder is an unsupervised algorithm.
The following diagram represents an autoencoder:

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