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Trends in Deep Learning Methodologies - Algorithms, Applications, and Systems (Paperback) Loot Price: R3,205
Discovery Miles 32 050
Trends in Deep Learning Methodologies - Algorithms, Applications, and Systems (Paperback): Vincenzo Piuri, Sandeep Raj, Angelo...

Trends in Deep Learning Methodologies - Algorithms, Applications, and Systems (Paperback)

Vincenzo Piuri, Sandeep Raj, Angelo Genovese, Rajshree Srivastava

Series: Hybrid Computational Intelligence for Pattern Analysis and Understanding

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Loot Price R3,205 Discovery Miles 32 050 | Repayment Terms: R300 pm x 12*

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Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models.

General

Imprint: Academic Press Inc
Country of origin: United States
Series: Hybrid Computational Intelligence for Pattern Analysis and Understanding
Release date: November 2020
First published: 2021
Editors: Vincenzo Piuri • Sandeep Raj • Angelo Genovese • Rajshree Srivastava
Dimensions: 229 x 152 x 20mm (L x W x T)
Format: Paperback
Pages: 306
ISBN-13: 978-0-12-822226-3
Categories: Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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LSN: 0-12-822226-3
Barcode: 9780128222263

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