Metaheuristics in Machine Learning Theory and Applications is popular PDF and ePub book, written by Diego Oliva in 2024-06-29, it is a fantastic choice for those who relish reading online the Computational intelligence genre. Let's immerse ourselves in this engaging Computational intelligence book by exploring the summary and details provided below. Remember, Metaheuristics in Machine Learning Theory and Applications can be Read Online from any device for your convenience.
Metaheuristics in Machine Learning Theory and Applications Book PDF Summary
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.
Detail Book of Metaheuristics in Machine Learning Theory and Applications PDF
- Author : Diego Oliva
- Release : 29 June 2024
- Publisher : Springer Nature
- ISBN : 9783030705428
- Genre : Computational intelligence
- Total Page : 765 pages
- Language : English
- PDF File Size : 9,7 Mb
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