Machine Learning and Metaheuristic Computation
eBook - PDF

Machine Learning and Metaheuristic Computation

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Machine Learning and Metaheuristic Computation

About this book

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.

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Yes, you can access Machine Learning and Metaheuristic Computation by Erik Cuevas,Jorge Galvez,Omar Avalos,Fernando Wario in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Contents
  5. About the Authors
  6. Preface
  7. Acknowledgments
  8. Introduction
  9. Chapter 1 Fundamentals of Machine Learning
  10. Chapter 2 Introduction to Metaheuristics Methods
  11. Chapter 3 Fundamental Machine Learning Methods
  12. Chapter 4 Main Metaheuristic Techniques
  13. Chapter 5 Metaheuristic Techniques for Fine‐Tuning Parameter of Complex Systems
  14. Chapter 6 Techniques of Machine Learning for Producing Metaheuristic Operators
  15. Chapter 7 Techniques of Machine Learning for Modifying the Search Strategy
  16. Chapter 8 Techniques of Machine Learning Mixed with Metaheuristic Methods
  17. Chapter 9 Metaheuristic Methods for Classification
  18. Chapter 10 Metaheuristic Methods for Clustering
  19. Chapter 11 Metaheuristic Methods for Dimensional Reduction
  20. Chapter 12 Metaheuristic Methods for Regression
  21. Index
  22. EULA