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Machine Learning for Edge Computing : Frameworks, Patterns and Best Practices
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Machine Learning for Edge Computing : Frameworks, Patterns and Best Practices
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Machine Learning for Edge Computing: Frameworks, Patterns and Best Practices
Published by Taylor & Francis Ltd, 2024
ISBN 10: 0367698331 ISBN 13: 9780367698331
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 370.
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Machine Learning for Edge Computing (Edge AI in Future Computing)
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Machine Learning for Edge Computing : Frameworks, Patterns and Best Practices
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Machine Learning for Edge Computing: Frameworks, Patterns and Best Practices
Published by Taylor & Francis Ltd, 2022
ISBN 10: 0367694328 ISBN 13: 9780367694326
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Hardback. Condition: New. New copy - Usually dispatched within 4 working days. 185.
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Machine Learning for Edge Computing : Frameworks, Patterns and Best Practices
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Machine Learning for Edge Computing (Paperback)
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 0367698331 ISBN 13: 9780367698331
Language: English
Paperback. Condition: new. Paperback. This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it discusses how to build AI models, i.e., model training and inference, on edge. This book provides insights into this new inter-disciplinary field of edge computing from a broader vision and perspective. The authors discuss machine learning algorithms for edge computing as well as the future needs and potential of the technology. The authors also explain the core concepts, frameworks, patterns, and research roadmap, which offer the necessary background for potential future research programs in edge intelligence.The target audience of this book includes academics, research scholars, industrial experts, scientists, and postgraduate students who are working in the field of Internet of Things (IoT) or edge computing and would like to add machine learning to enhance the capabilities of their work. This book explores the following topics: Edge computing, hardware for edge computing AI, and edge virtualization techniques Edge intelligence and deep learning applications, training, and optimization Machine learning algorithms used for edge computing Reviews AI on IoT Discusses future edge computing needsAmitoj Singh is an Associate Professor at the School of Sciences of Emerging Technologies, Jagat Guru Nanak Dev Punjab State Open University, Punjab, India.Vinay Kukreja is a Professor at the Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, India.Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran. This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it also discusses how to build AI models, i.e., model training and inference, on edge. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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£ 97.28
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Machine Learning for Edge Computing (Edge AI in Future Computing)
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Machine Learning for Edge Computing : Frameworks, Patterns and Best Practices
Published by Taylor & Francis Ltd (Sales) Jul 2022, 2022
ISBN 10: 0367694328 ISBN 13: 9780367694326
Language: English
£ 120.37
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Add to basketBuch. Condition: Neu. Neuware - This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it also discusses how to build AI models, i.e., model training and inference, on edge.
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Machine Learning for Edge Computing (Paperback)
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 0367698331 ISBN 13: 9780367698331
Language: English
£ 97.99
Convert currency£ 37.22 shipping from U.S.A. to United KingdomQuantity: 1 available
Add to basketPaperback. Condition: new. Paperback. This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it discusses how to build AI models, i.e., model training and inference, on edge. This book provides insights into this new inter-disciplinary field of edge computing from a broader vision and perspective. The authors discuss machine learning algorithms for edge computing as well as the future needs and potential of the technology. The authors also explain the core concepts, frameworks, patterns, and research roadmap, which offer the necessary background for potential future research programs in edge intelligence.The target audience of this book includes academics, research scholars, industrial experts, scientists, and postgraduate students who are working in the field of Internet of Things (IoT) or edge computing and would like to add machine learning to enhance the capabilities of their work. This book explores the following topics: Edge computing, hardware for edge computing AI, and edge virtualization techniques Edge intelligence and deep learning applications, training, and optimization Machine learning algorithms used for edge computing Reviews AI on IoT Discusses future edge computing needsAmitoj Singh is an Associate Professor at the School of Sciences of Emerging Technologies, Jagat Guru Nanak Dev Punjab State Open University, Punjab, India.Vinay Kukreja is a Professor at the Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, India.Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran. This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it also discusses how to build AI models, i.e., model training and inference, on edge. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Machine Learning for Edge Computing (Paperback)
Published by Taylor & Francis Ltd, London, 2024
ISBN 10: 0367698331 ISBN 13: 9780367698331
Language: English
£ 118.37
Convert currency£ 27.54 shipping from Australia to United KingdomQuantity: 1 available
Add to basketPaperback. Condition: new. Paperback. This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it discusses how to build AI models, i.e., model training and inference, on edge. This book provides insights into this new inter-disciplinary field of edge computing from a broader vision and perspective. The authors discuss machine learning algorithms for edge computing as well as the future needs and potential of the technology. The authors also explain the core concepts, frameworks, patterns, and research roadmap, which offer the necessary background for potential future research programs in edge intelligence.The target audience of this book includes academics, research scholars, industrial experts, scientists, and postgraduate students who are working in the field of Internet of Things (IoT) or edge computing and would like to add machine learning to enhance the capabilities of their work. This book explores the following topics: Edge computing, hardware for edge computing AI, and edge virtualization techniques Edge intelligence and deep learning applications, training, and optimization Machine learning algorithms used for edge computing Reviews AI on IoT Discusses future edge computing needsAmitoj Singh is an Associate Professor at the School of Sciences of Emerging Technologies, Jagat Guru Nanak Dev Punjab State Open University, Punjab, India.Vinay Kukreja is a Professor at the Chitkara Institute of Engineering and Technology, Chitkara University, Punjab, India.Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran. This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it also discusses how to build AI models, i.e., model training and inference, on edge. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Hardcover. Condition: Brand New. 184 pages. 9.18x6.12x0.50 inches. In Stock.
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Machine Learning for Edge Computing
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Paperback. Condition: Brand New. 200 pages. 9.18x6.12x9.21 inches. In Stock. This item is printed on demand.
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£ 99.19
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Add to basketPAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Machine Learning for Edge Computing: Frameworks, Patterns and Best Practices
Published by Taylor & Francis Ltd, 2022
ISBN 10: 0367694328 ISBN 13: 9780367694326
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
