Metaheuristics in Machine Learning: Theory and Applications

Released on by Diego Oliva
preview-18

  • Metaheuristics in Machine Learning: Theory and Applications Book Detail

  • Author : Diego Oliva
  • Release Date :
  • Publisher : Springer Nature
  • Genre : Computational intelligence
  • Pages : 765
  • ISBN 13 : 3030705420
  • File Size : 9,9 MB
DOWNLOAD BOOK

Metaheuristics in Machine Learning: Theory and Applications by Diego Oliva PDF Summary

Book Description: 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.

Disclaimer: www.yourbookbest.com does not own Metaheuristics in Machine Learning: Theory and Applications books pdf, neither created or scanned. We just provide the link that is already available on the internet, public domain and in Google Drive. If any way it violates the law or has any issues, then kindly mail us via contact us page to request the removal of the link.

Evolutionary Computation

Evolutionary Computation

File Size : 84,84 MB
Total View : 8520 Views
DOWNLOAD

Edited by professionals with years of experience, this book provides an introduction to the theory of evolutionary algorithms and single- and multi-objective op