Optimization in Machine Learning and Applications (Hardcover, 1st ed. 2020)

This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Algorithms for Intelligent Systems
Release date:	December 2019
First published:	2020
Editors:	Anand J. Kulkarni • Suresh Chandra Satapathy
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	197
Edition:	1st ed. 2020
ISBN-13:	978-981-15-0993-3
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	981-15-0993-X
Barcode:	9789811509933

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