February 2019
Intermediate to advanced
386 pages
9h 54m
English
Content preview from Hands-On Unsupervised Learning with Python
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Unsupervised deep belief networks
In this section, we will discuss a very famous generative model that, in an unsupervised scenario, can be employed in order to perform the dimensionality reduction of input dataset X, drawn from a predefined data-generating process. As this book has no particular prerequisites and the mathematical complexity is quite high, we are going to briefly introduce the concepts, without proofs, nor a deep analysis of the structures of the algorithms. Before discussing deep belief networks (DBN), it's necessary to introduce another model, the Restricted Boltzmann Machine (RBM), which can be considered a building block for a DBN.
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