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Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation

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Algorithms in Machine Learning Paradigms (Hardcover, 1st ed. 2020) Loot Price: R4,696
Discovery Miles 46 960
Repayment Terms: R440 pm x 12*
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Algorithms in Machine Learning Paradigms (Hardcover, 1st ed. 2020): Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Paramartha...

Algorithms in Machine Learning Paradigms (Hardcover, 1st ed. 2020)

Jyotsna Kumar Mandal, Somnath Mukhopadhyay, Paramartha Dutta, Kousik Dasgupta

Series: Studies in Computational Intelligence, 870

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Loot Price R4,696 Discovery Miles 46 960 | Repayment Terms: R440 pm x 12*

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This book presents studies involving algorithms in the machine learning paradigms. It discusses a variety of learning problems with diverse applications, including prediction, concept learning, explanation-based learning, case-based (exemplar-based) learning, statistical rule-based learning, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence-based learning.

General

Imprint: Springer Verlag, Singapore
Country of origin: Singapore
Series: Studies in Computational Intelligence, 870
Release date: 2020
First published: 2020
Editors: Jyotsna Kumar Mandal • Somnath Mukhopadhyay • Paramartha Dutta • Kousik Dasgupta
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 195
Edition: 1st ed. 2020
ISBN-13: 978-981-15-1040-3
Categories: Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation
Books > Computing & IT > Applications of computing > Image processing > General
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
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LSN: 981-15-1040-7
Barcode: 9789811510403

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