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Deep Learning - Research and Applications (Hardcover) Loot Price: R4,094
Discovery Miles 40 940
Deep Learning - Research and Applications (Hardcover): Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal...

Deep Learning - Research and Applications (Hardcover)

Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy

Series: De Gruyter Frontiers in Computational Intelligence

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Loot Price R4,094 Discovery Miles 40 940 | Repayment Terms: R384 pm x 12*

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This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition.

General

Imprint: De Gruyter
Country of origin: Germany
Series: De Gruyter Frontiers in Computational Intelligence
Release date: June 2020
First published: 2020
Editors: Siddhartha Bhattacharyya • Vaclav Snasel • Aboul Ella Hassanien • Satadal Saha • B. K. Tripathy
Dimensions: 170 x 240mm (L x W)
Format: Hardcover - Cloth over boards
Pages: 161
ISBN-13: 978-3-11-067079-0
Categories: Books > Computing & IT > General theory of computing > Data structures
Books > Computing & IT > Computer programming > Algorithms & procedures
Books > Computing & IT > Applications of computing > Pattern recognition
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics
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LSN: 3-11-067079-8
Barcode: 9783110670790

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