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Synopsis
This book discusses state-of-the-art reviews of the existing machine-learning techniques and algorithms including hybridizations and optimizations. It is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Tanvir Habib Sardar is an Assistant Professor in the department of CSE at GITAM University, Bengaluru campus. He has more than fifteen years of experience in industry and academia. His research domain is big data, machine learning, fuzzy logic, and distributed computing using MapReduce.
Bishwajeet Kumar Pandey is a Professor at Department of Intelligent System and Cyber Security, Astana IT University Kazaksthan. He is also a visiting professor at Eurasian National University, Astana, Kazaksthan (QS World Rank 355) and UCSI University, Kuala Lumpur, Malaysia (QS World Rank 300). He has interest in Green Computing, High-Performance Computing, Cyber-Physical Systems, Machine Learning, and Cyber Security.
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Machine Learning Hybridization and Optimization for Intelligent Applications (Computational Intelligence Techniques)
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Machine Learning Hybridization and Optimization for Intelligent Applications (Computational Intelligence Techniques)
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Machine Learning Hybridization and Optimization for Intelligent Applications
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Machine Learning Hybridization and Optimization for Intelligent Applications (Hardcover)
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Taylor & Francis Ltd, London, 2024
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Hardcover. Etat : new. Hardcover. This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation.Features:Focuses on hybridization and optimization of machine learning techniquesReviews supervised, unsupervised, and reinforcement learning using case study-based applicationsCovers the latest machine learning applications in as diverse domains as the Internet of Things, data science, cloud computing, and distributed and parallel computingExplains computing models using real-world examples and dataset-based experimentsIncludes case study-based explanations and usage for machine learning technologies and applicationsThis book is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering. This book discusses state-of-the-art reviews of the existing machine-learning techniques and algorithms including hybridizations and optimizations. It is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781032737539
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Machine Learning Hybridization and Optimization for Intelligent Applications
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CRC Press, 2024
ISBN 10 : 1032737530
ISBN 13 : 9781032737539
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Machine Learning Hybridization and Optimization for Intelligent Applications (Computational Intelligence Techniques)
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Machine Learning Hybridization and Optimization for Intelligent Applications
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Machine Learning Hybridization and Optimization for Intelligent Applications (Computational Intelligence Techniques)
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Machine Learning Hybridization and Optimization for Intelligent Applications (Computational Intelligence Techniques)
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Machine Learning Hybridization and Optimization for Intelligent Applications
Edité par
CRC Press, 2024
ISBN 10 : 1032737530
ISBN 13 : 9781032737539
Ancien ou d'occasion
Couverture rigide
Vendeur : GreatBookPricesUK, Woodford Green, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 47625444
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