Machine Learning for Edge Computing: Frameworks, Patterns and Best Practices

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.

本書將邊緣智能分為邊緣人工智能（智能化邊緣運算）和邊緣上的人工智能（邊緣上的人工智能）。它專注於通過有效的人工智能技術為邊緣運算的關鍵問題提供最佳解決方案，並討論如何在邊緣上建立人工智能模型，即模型訓練和推理。本書從更廣泛的視野和角度提供了對這個新的跨學科邊緣運算領域的深入見解。作者們討論了邊緣運算的機器學習算法以及該技術的未來需求和潛力。作者還解釋了核心概念、框架、模式和研究路線圖，為邊緣智能的潛在未來研究項目提供了必要的背景。

本書的目標讀者包括學者、研究學者、工業專家、科學家和研究生，他們在物聯網（IoT）或邊緣運算領域工作，並希望通過添加機器學習來增強其工作能力。

本書探討以下主題：
- 邊緣運算、邊緣運算人工智能的硬體和邊緣虛擬化技術
- 邊緣智能和深度學習應用、訓練和優化
- 用於邊緣運算的機器學習算法
- 評論物聯網上的人工智能，討論未來邊緣運算的需求

Amitoj Singh是印度旁遮普邦Jagat Guru Nanak Dev Punjab State Open University新興技術學院的副教授。

Vinay Kukreja是印度旁遮普邦Chitkara大學Chitkara工程與技術學院的教授。

Taghi Javdani Gandomani是伊朗Shahrekord大學的助理教授。

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.

Amitoj Singh在印度旁遮普邦巴蒂達的MRSPTU（Maharaja Ranjit Singh Punjab Technical University）擔任計算科學系的助理教授。

Vinay Kukreja在印度旁遮普邦的Chitkara大學擔任副教授。

Taghi Javdani Gandomani是伊朗沙赫雷克爾德的沙赫雷克爾德大學的助理教授。