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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 417 | Sprache: Englisch | Produktart: Bücher | This book explains the importance of AI mathematical optimization. It covers AI optimization's fundamental concepts, methodologies, and practical applications in machine learning, automation, NLP, and real-world scenarios. The described optimization.
Condition: Hervorragend. Zustand: Hervorragend | Seiten: 417 | Sprache: Englisch | Produktart: Bücher | This book explains the importance of AI mathematical optimization. It covers AI optimization's fundamental concepts, methodologies, and practical applications in machine learning, automation, NLP, and real-world scenarios. The described optimization.
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Buch. Condition: Neu. Math Optimization for Artificial Intelligence | Heuristic and Metaheuristic Methods for Robotics and Machine Learning | Umesh Kumar Lilhore (u. a.) | Buch | XIII | Englisch | 2025 | De Gruyter | EAN 9783111436050 | Verantwortliche Person für die EU: Walter de Gruyter GmbH, De Gruyter GmbH, Genthiner Str. 13, 10785 Berlin, productsafety[at]degruyterbrill[dot]com | Anbieter: preigu.
Buch. Condition: Neu. Neuware - The book presents powerful optimization approaches for integrating AI into daily life.This book explores how heuristic and metaheuristic methodologies have revolutionized the fields of robotics and machine learning. The book covers the wide range of tools and methods that have emerged as part of the AI revolution, from state-of-the-art decision-making algorithms for robots to data-driven machine learning models. Each chapter offers a meticulous examination of the theoretical foundations and practical applications of mathematical optimization, helping readers understand how these methods are transforming the field of technology.This book is an invaluable resource for researchers, practitioners, and students. It makes AI optimization accessible and comprehensible, equipping the next generation of innovators with the knowledge and skills to further advance robotics and machine learning. While artificial intelligence constantly evolves, this book sheds light on the path ahead.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In contemporary engineering domains, optimization and decision-making issues are crucial. Given the vast amounts of available data, processing times and memory usage can be substantial. Developing and implementing novel heuristic algorithms is time-consuming, yet even minor improvements in solutions can significantly reduce computational costs. In such scenarios, the creation of heuristics and metaheuristic algorithms has proven advantageous. The convergence of machine learning and metaheuristic algorithms offers a promising approach to address these challenges. Metaheuristic and Machine Learning Optimization Strategies for Complex Systems covers all areas of comprehensive information about hyper-heuristic models, hybrid meta-heuristic models, nature-inspired computing models, and meta-heuristic models. The key contribution of this book is the construction of a hyper-heuristic approach for any general problem domain from a meta-heuristic algorithm. Covering topics such as cloud computing, internet of things, and performance evaluation, this book is an essential resource for researchers, postgraduate students, educators, data scientists, machine learning engineers, software developers and engineers, policy makers, and more.
Seller: AHA-BUCH GmbH, Einbeck, Germany
Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In contemporary engineering domains, optimization and decision-making issues are crucial. Given the vast amounts of available data, processing times and memory usage can be substantial. Developing and implementing novel heuristic algorithms is time-consuming, yet even minor improvements in solutions can significantly reduce computational costs. In such scenarios, the creation of heuristics and metaheuristic algorithms has proven advantageous. The convergence of machine learning and metaheuristic algorithms offers a promising approach to address these challenges. Metaheuristic and Machine Learning Optimization Strategies for Complex Systems covers all areas of comprehensive information about hyper-heuristic models, hybrid meta-heuristic models, nature-inspired computing models, and meta-heuristic models. The key contribution of this book is the construction of a hyper-heuristic approach for any general problem domain from a meta-heuristic algorithm. Covering topics such as cloud computing, internet of things, and performance evaluation, this book is an essential resource for researchers, postgraduate students, educators, data scientists, machine learning engineers, software developers and engineers, policy makers, and more.