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Více informací o knize Metaheuristics in Machine Learning: Theory and Applications

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Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Metaheuristics in Machine Learning: Theory and Applications
• Autor: Diego Oliva, Essam H. Houssein, Salvador Hinojosa
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 769
• EAN: 9783030705442
• ID: 39335800
• Nakladatelství: Springer Nature Switzerland AG
• Hmotnost: 1187 g
• Rozměry: 235 × 155 × 42 mm
• Datum vydání: 15. July 2022

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