Introduction to Deep Learning

Collins Achepsah Leke; Tshilidzi Marwala

doi:10.1007/978-3-030-01180-2_2

Introduction to Deep Learning

Collins Achepsah Leke, Tshilidzi Marwala

Faculty of Engineering and the Built Environment

University of Johannesburg

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

This chapter presents information on deep learning. It describes the building blocks of the first breakthrough in deep neural networks being the deep belief neural network. These are the restricted Boltzmann machine and the contrastive divergence algorithm. Subsequently, the deep belief, convolutional, recurrent and deep autoencoder neural networks are presented, followed by concluding remarks.

Original language	English
Title of host publication	Studies in Big Data
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	21-40
Number of pages	20
DOIs	https://doi.org/10.1007/978-3-030-01180-2_2
Publication status	Published - 2019

Publication series

Name	Studies in Big Data
Volume	48
ISSN (Print)	2197-6503
ISSN (Electronic)	2197-6511

ASJC Scopus subject areas

Control and Systems Engineering
Engineering (miscellaneous)
Computer Science Applications
Artificial Intelligence

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10.1007/978-3-030-01180-2_2

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Introduction to Deep Learning

Abstract

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