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    Metaheuristics in Machine Learning: Theory and Applications

Metaheuristics in Machine Learning: Theory and Applications

Diego Oliva
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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. 
      Format: Paperback / softback CONTRIBUTORS: Diego Oliva EAN: 9783030705442 COUNTRY: Switzerland PAGES: WEIGHT: 1187 g HEIGHT: 235 cm
      PUBLISHED BY: Springer Nature Switzerland AG DATE PUBLISHED: 2022-07-15 CITY: GENRE: COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Engineering (General) WIDTH: 155 cm SPINE:

      Book Themes:

      Artificial intelligence, Machine learning

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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. 
      Format: Paperback / softback CONTRIBUTORS: Diego Oliva EAN: 9783030705442 COUNTRY: Switzerland PAGES: WEIGHT: 1187 g HEIGHT: 235 cm
      PUBLISHED BY: Springer Nature Switzerland AG DATE PUBLISHED: 2022-07-15 CITY: GENRE: COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Engineering (General) WIDTH: 155 cm SPINE:

      Book Themes:

      Artificial intelligence, Machine learning

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      Be the first to write a review
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