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Synopsis
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 needs
Amitoj 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.
"synopsis" may belong to another edition of this title.
About the Author
Amitoj Singh is working as Assistant Professor in the department of Computational Sciences, MRSPTU, Bathinda, Punjab, India.
Vinay Kukreja is working as an Associate professor at Chitkara University, Punjab, India.
Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran.
"About this title" may belong to another edition of this title.
- PublisherCRC Press
- Publication date2024
- ISBN 10 0367698331
- ISBN 13 9780367698331
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages200
- EditorSingh Amitoj, Kukreja Vinay, Gandomani Taghi Javdani
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Machine Learning for Edge Computing : Frameworks, Patterns and Best Practices
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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 multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780367698331
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