Metaheuristics in Machine Learning: Theory and Applications

Know about the book -

Metaheuristics in Machine Learning: Theory and Applications is written by Diego Oliva and published by Springer Nature. It's available with International Standard Book Number or ISBN identification 3030705420 (ISBN 10) and 9783030705428 (ISBN 13).

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.