Model Optimization Methods For Efficient And Edge Ai
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Model Optimization Methods For Efficient And Edge Ai
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Author : Pethuru Raj Chelliah
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-09
Model Optimization Methods For Efficient And Edge Ai written by Pethuru Raj Chelliah and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-09 with Computers categories.
Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural approaches, enabling frameworks, and applications Model Optimization Methods for Efficient and Edge AI explores AI model engineering, evaluation, refinement, optimization, and deployment across multiple cloud environments (public, private, edge, and hybrid). It presents key applications of the AI paradigm, including computer vision (CV) and Natural Language Processing (NLP), explaining the nitty-gritty of federated learning (FL) and how the FL method is helping to fulfill AI model optimization needs. The book also describes tools that vendors have created, including FL frameworks and platforms such as PySyft, Tensor Flow Federated (TFF), FATE (Federated AI Technology Enabler), Tensor/IO, and more. The first part of the text covers popular AI and ML methods, platforms, and applications, describing leading AI frameworks and libraries in order to clearly articulate how these tools can help with visualizing and implementing highly flexible AI models quickly. The second part focuses on federated learning, discussing its basic concepts, applications, platforms, and its potential in edge systems (such as IoT). Other topics covered include: Building AI models that are destined to solve several problems, with a focus on widely articulated classification, regression, association, clustering, and other prediction problems Generating actionable insights through a variety of AI algorithms, platforms, parallel processing, and other enablers Compressing AI models so that computational, memory, storage, and network requirements can be substantially reduced Addressing crucial issues such as data confidentiality, data access rights, data protection, and access to heterogeneous data Overcoming cyberattacks on mission-critical software systems by leveraging federated learning
Integrating Ai And Sustainability In Technical And Vocational Education And Training Tvet
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Author : Sorayyaei Azar, Ali
language : en
Publisher: IGI Global
Release Date : 2025-04-24
Integrating Ai And Sustainability In Technical And Vocational Education And Training Tvet written by Sorayyaei Azar, Ali and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-24 with Education categories.
As industries worldwide adopt advanced technologies and sustainable practices, the role of technical and vocational education and training (TVET) is evolving to meet these new demands. TVET institutions must now integrate artificial intelligence (AI) and sustainability into their programs to produce a workforce equipped with future-ready skills. By incorporating AI tools and sustainable practices into TVET curricula, educators can provide learners with the competencies to thrive in green technologies, smart manufacturing, renewable energy, and other emerging fields. This integration empowers individuals with new skills and contributes to a more sustainable, resilient global economy. Further exploration may bridge the gap between technological advancement and environmental responsibility. Integrating AI and Sustainability in Technical and Vocational Education and Training (TVET) provides a comprehensive guide on how TVET can successfully incorporate technological elements, addressing the frameworks, strategies, best practices, and challenges associated with this transformation. It supports educators in navigating the complexities of integrating AI and sustainability into vocational training. This book covers topics such as cybersecurity, data science, and supply chains, and is a useful resource for business owners, engineers, educators, academicians, researchers, and data scientists.
Ai Enabled Sustainable Innovations In Education And Business
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Author : Sorayyaei Azar, Ali
language : en
Publisher: IGI Global
Release Date : 2025-04-24
Ai Enabled Sustainable Innovations In Education And Business written by Sorayyaei Azar, Ali and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-24 with Computers categories.
Sustainability for the future is an ever-present concern. Modern innovations in education and business are enhancing resources and technology for improved sustainability-driven solutions. Artificial intelligence (AI), specifically, is transforming education and business by providing real-time data processing systems for decision support and streamlining processes. As a result, educators and business leaders are better able to allocate resources and maximize their impact on students, industries, and customers in addition to sustainability. By fostering efficiency and sustainability in education and business, AI may also increase individual environmental awareness and social responsibility. AI-Enabled Sustainable Innovations in Education and Business discusses technological advancements in digital education and learning, and in various industries, including healthcare, finance, and supply chains. It highlights advanced innovations for environmental, economic, and operational sustainability. Covering topics such as information and communication technology (ICT), state government programs, and automated device management, this book is an excellent resource for business leaders, executives, managers, educators, school administrators, technologists, computer engineers, sustainability advocates, professionals, researchers, scholars, academicians, and more.
Modernizing The Food Industry Ai Powered Infrastructure Security And Supply Chain Innovation
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Author : Whig, Pawan
language : en
Publisher: IGI Global
Release Date : 2025-07-09
Modernizing The Food Industry Ai Powered Infrastructure Security And Supply Chain Innovation written by Whig, Pawan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-09 with Technology & Engineering categories.
The food industry has changed immensely with the integration of AI. AI-powered technologies are streamlining operations and enhance food safety. Smart systems can now predict demand and optimize logistics in real time. As global supply chains become more intricate and consumer expectations rise, modernizing the food industry with AI is not only a competitive advantage but a necessary evolution for resilience, sustainability, and long-term growth. Modernizing the Food Industry: AI-Powered Infrastructure, Security, and Supply Chain Innovation explores how AI is transforming the food industry by enhancing infrastructure efficiency, strengthening food security, and optimizing supply chain operations. It examines cutting-edge technologies and real-world applications that drive innovation, sustainability, and resilience across the global food ecosystem. Covering topics such as automation, food traceability, and nutrition, this book is an excellent resource for food industry professionals, supply chain managers, technology innovators, AI researchers, policymakers, academicians, and more.
Edge Ai
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Author : Xiaofei Wang
language : en
Publisher: Springer Nature
Release Date : 2020-08-31
Edge Ai written by Xiaofei Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-31 with Computers categories.
As an important enabler for changing people’s lives, advances in artificial intelligence (AI)-based applications and services are on the rise, despite being hindered by efficiency and latency issues. By focusing on deep learning as the most representative technique of AI, this book provides a comprehensive overview of how AI services are being applied to the network edge near the data sources, and demonstrates how AI and edge computing can be mutually beneficial. To do so, it introduces and discusses: 1) edge intelligence and intelligent edge; and 2) their implementation methods and enabling technologies, namely AI training and inference in the customized edge computing framework. Gathering essential information previously scattered across the communication, networking, and AI areas, the book can help readers to understand the connections between key enabling technologies, e.g. a) AI applications in edge; b) AI inference in edge; c) AI training for edge; d) edge computing for AI; and e) using AI to optimize edge. After identifying these five aspects, which are essential for the fusion of edge computing and AI, it discusses current challenges and outlines future trends in achieving more pervasive and fine-grained intelligence with the aid of edge computing.
Mobile Edge Artificial Intelligence
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Author : Yuanming Shi
language : en
Publisher: Elsevier
Release Date : 2021-08-17
Mobile Edge Artificial Intelligence written by Yuanming Shi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-17 with Computers categories.
Front Cover -- Mobile Edge Artificial Intelligence -- Copyright -- Contents -- List of figures -- Biography -- Yuanming Shi -- Kai Yang -- Zhanpeng Yang -- Yong Zhou -- Preface -- Acknowledgments -- Part 1 Introduction and overview -- 1 Motivations and organization -- 1.1 Motivations -- 1.2 Organization -- References -- 2 Primer on artificial intelligence -- 2.1 Basics of machine learning -- 2.1.1 Supervised learning -- 2.1.1.1 Logistic regression -- 2.1.1.2 Support vector machine -- 2.1.1.3 Decision tree -- 2.1.1.4 k-Nearest neighbors method -- 2.1.1.5 Neural network -- 2.1.2 Unsupervised learning -- 2.1.2.1 k-Means algorithm -- 2.1.2.2 Principal component analysis -- 2.1.2.3 Autoencoder -- 2.1.3 Reinforcement learning -- 2.1.3.1 Q-learning -- 2.1.3.2 Policy gradient -- 2.2 Models of deep learning -- 2.2.1 Convolutional neural network -- 2.2.2 Recurrent neural network -- 2.2.3 Graph neural network -- 2.2.4 Generative adversarial network -- 2.3 Summary -- References -- 3 Convex optimization -- 3.1 First-order methods -- 3.1.1 Gradient method for unconstrained problems -- 3.1.2 Gradient method for constrained problems -- 3.1.3 Subgradient descent method -- 3.1.4 Mirror descent method -- 3.1.5 Proximal gradient method -- 3.1.6 Accelerated gradient method -- 3.1.7 Smoothing for nonsmooth optimization -- 3.1.8 Dual and primal-dual methods -- 3.1.9 Alternating direction method of multipliers -- 3.1.10 Stochastic gradient method -- 3.2 Second-order methods -- 3.2.1 Newton's method -- 3.2.2 Quasi-Newton method -- 3.2.3 Gauss-Newton method -- 3.2.4 Natural gradient method -- 3.3 Summary -- References -- 4 Mobile edge AI -- 4.1 Overview -- 4.2 Edge inference -- 4.2.1 On-device inference -- 4.2.2 Edge inference via computation offloading -- 4.2.2.1 Server-based edge inference -- 4.2.2.2 Device-edge joint inference -- 4.3 Edge training.
Deep Learning Model Optimization Deployment And Improvement Techniques For Edge Native Applications
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Author : Pethuru Raj
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2024-08-22
Deep Learning Model Optimization Deployment And Improvement Techniques For Edge Native Applications written by Pethuru Raj and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-22 with Computers categories.
The edge AI implementation technologies are fast maturing and stabilizing. Edge AI digitally transforms retail, manufacturing, healthcare, financial services, transportation, telecommunication, and energy. The transformative potential of Edge AI, a pivotal force in driving the evolution from Industry 4.0’s smart manufacturing and automation to Industry 5.0’s human-centric, sustainable innovation. The exploration of the cutting-edge technologies, tools, and applications that enable real-time data processing and intelligent decision-making at the network’s edge, addressing the increasing demand for efficiency, resilience, and personalization in industrial systems. Our book aims to provide readers with a comprehensive understanding of how Edge AI integrates with existing infrastructures, enhances operational capabilities, and fosters a symbiotic relationship between human expertise and machine intelligence. Through detailed case studies, technical insights, and practical guidelines, this book serves as an essential resource for professionals, researchers, and enthusiasts poised to harness the full potential of Edge AI in the rapidly advancing industrial landscape.
Ai On The Edge With Security
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Author : Naresh Kumar Sehgal
language : en
Publisher: Springer Nature
Release Date : 2024-12-24
Ai On The Edge With Security written by Naresh Kumar Sehgal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-24 with Computers categories.
This book provides readers with an overview of the next generation of Cloud computing with AI, evolving to minimize latency and address privacy/security concerns of many customers. This book will highlight the associated problems and propose new solutions for performing AI and ML at the edge of computing networks.
Quantum Machine Learning
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Author : Pethuru Raj
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-08-05
Quantum Machine Learning written by Pethuru Raj and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-05 with Computers categories.
Quantum computing has shown a potential to tackle specific types of problems, especially those involving a daunting number of variables, at an exponentially faster rate compared to classical computers. This volume focuses on quantum variants of machine learning algorithms, such as quantum neural networks, quantum reinforcement learning, quantum principal component analysis, quantum support vectors, quantum Boltzmann machines, and many more.
Scalable Artificial Intelligence For Healthcare
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Author : Houneida Sakly
language : en
Publisher: CRC Press
Release Date : 2025-05-06
Scalable Artificial Intelligence For Healthcare written by Houneida Sakly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-06 with Computers categories.
This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility. The content provides a comprehensive exploration of the principles and practices required to scale AI applications in healthcare, addressing areas such as diagnosis, treatment, and patient care. Key topics include data scalability, model deployment, and infrastructure design, highlighting the use of microservices, containerization, cloud computing, and big data technologies in building scalable AI systems. Discussions cover advancements in machine learning models, distributed processing, and transfer learning, alongside critical considerations such as continuous integration, data privacy, and ethics. Real-world case studies depict both the successes and challenges of implementing scalable AI across various healthcare environments, offering valuable insights for future advancements. This volume serves as a practical and theoretical guide for healthcare professionals, AI researchers, and technology enthusiasts seeking to develop or expand on AI-driven healthcare solutions to address global health challenges effectively.