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Optimization algorithms in machine l...
~
Das, Debashish.
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Optimization algorithms in machine learning = a meta-heuristics perspective /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Optimization algorithms in machine learning/ by Debashish Das, Ali Safaa Sadiq, Seyedali Mirjalili.
Reminder of title:
a meta-heuristics perspective /
Author:
Das, Debashish.
other author:
Sadiq, Ali Safaa.
Published:
Singapore :Springer Nature Singapore : : 2025.,
Description:
xvii, 181 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:
Challenges and opportunities in Machine Learning using optimization techniques -- Optimization methods: traditional versus stochastic -- Heuristic and meta-heuristic optimization algorithms -- A comprehensive review of evolutionary algorithms and swarm intelligence methods -- Artificial Neural Networks: structure and learning -- A survey of Neural Networks trained by optimization algorithms and meta-heuristics.
Contained By:
Springer Nature eBook
Subject:
Machine learning. -
Online resource:
https://doi.org/10.1007/978-981-96-3849-9
ISBN:
9789819638499
Optimization algorithms in machine learning = a meta-heuristics perspective /
Das, Debashish.
Optimization algorithms in machine learning
a meta-heuristics perspective /[electronic resource] :by Debashish Das, Ali Safaa Sadiq, Seyedali Mirjalili. - Singapore :Springer Nature Singapore :2025. - xvii, 181 p. :ill. (some col.), digital ;24 cm. - Engineering optimization: methods and applications,2731-4057. - Engineering optimization: methods and applications..
Challenges and opportunities in Machine Learning using optimization techniques -- Optimization methods: traditional versus stochastic -- Heuristic and meta-heuristic optimization algorithms -- A comprehensive review of evolutionary algorithms and swarm intelligence methods -- Artificial Neural Networks: structure and learning -- A survey of Neural Networks trained by optimization algorithms and meta-heuristics.
This book explores the development of several new learning algorithms that utilize recent optimization techniques and meta-heuristics. It addresses well-known models such as particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, population-based incremental learning, and grey wolf optimizer for training neural networks. Additionally, the book examines the challenges associated with these processes in detail. This volume will serve as a valuable reference for individuals in both academia and industry.
ISBN: 9789819638499
Standard No.: 10.1007/978-981-96-3849-9doiSubjects--Topical Terms:
533906
Machine learning.
LC Class. No.: Q325.5
Dewey Class. No.: 006.31
Optimization algorithms in machine learning = a meta-heuristics perspective /
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Intelligent Technologies and Robotics (SpringerNature-42732)
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