Metaheuristics in Machine Learning: Theory and Applications

Metaheuristics in Machine Learning: Theory and Applications
Author: Diego Oliva
Publisher: Springer Nature
Total Pages: 765
Release:
Genre: Computational intelligence
ISBN: 3030705420


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This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.


Metaheuristics in Machine Learning: Theory and Applications
Language: en
Pages: 765
Authors: Diego Oliva
Categories: Computational intelligence
Type: BOOK - Published: - Publisher: Springer Nature

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This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that em
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