Machine Learning and Metaheuristic Computation

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Erik Cuevas (University of Guadalajara, Mexico; Freie Universität Berlin, Germany) Jorge Galvez

Machine Learning and Metaheuristic Computation

Erik Cuevas (University of Guadalajara, Mexico; Freie Universität Berlin, Germany), Jorge Galvez, Omar Avalos , Fernando Wario

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English

Wiley-IEEE Press
31 October 2024

Data capture & analysis; Data mining; Machine learning

Learn to bridge the gap between machine learning and metaheuristic methods to solve problems in optimization approaches

Few areas of technology have greater potential to revolutionize the globe than artificial intelligence. Two key areas of artificial intelligence, machine learning and metaheuristic computation, have an enormous range of individual and combined applications in computer science and technology. To date, these two complementary paradigms have not always been treated together, despite the potential of a combined approach which maximizes the utility and minimizes the drawbacks of both.

Machine Learning and Metaheuristic Computation offers an introduction to both of these approaches and their joint applications. Both a reference text and a course, it is built around the popular Python programming language to maximize utility. It guides the reader gradually from an initial understanding of these crucial methods to an advanced understanding of cutting-edge artificial intelligence tools.

The text also provides:

Treatment suitable for readers with only basic mathematical training Detailed discussion of topics including dimensionality reduction, clustering methods, differential evolution, and more A rigorous but accessible vision of machine learning algorithms and the most popular approaches of metaheuristic optimization

Machine Learning and Metaheuristic Computation is ideal for students, researchers, and professionals looking to combine these vital methods to solve problems in optimization approaches.

By: Erik Cuevas (University of Guadalajara Mexico; Freie Universität Berlin Germany), Jorge Galvez, Omar Avalos, Fernando Wario
Imprint: Wiley-IEEE Press
Country of Publication: United States
ISBN: 9781394229642
ISBN 10: 139422964X
Pages: 432
Publication Date: 31 October 2024
Audience: Professional and scholarly , College/higher education , Undergraduate , Further / Higher Education
Format: Hardback
Publisher's Status: Active

Erik Cuevas, PhD, is a Full Professor in the Department of Electronics at the University of Guadalajara. He is a Member of the Mexican Academy of Sciences and the National System of Researchers. He has provided editorial services on several specialized journals. Jorge Galvez, PhD, is a Full Professor in the Department of Innovation Based on Information and Knowledge at the University of Guadalajara. He is a Member of the Mexican Academy of Sciences and the National System of Researchers. Omar Avalos, PhD, is a Professor in the Electronics and Computing Division of the University Center for Exact Sciences and Engineering at the University of Guadalajara. He is a Member of the Mexican Academy of Sciences and the National System of Researchers. Fernando Wario, PhD, is a Professor at the University of Guadalajara and an Associate Researcher at the Institute of Cognitive Sciences and Technologies (ISTC) in Rome, Italy. He is a Member of the Mexican Academy of Sciences and the National System of Researchers.