Deep Learning Model Optimization Deployment And Improvement Techniques For Edge Native Applications
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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.
Building Scalable Edge Ai Solutions For The Internet Of Things
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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Building Scalable Edge Ai Solutions For The Internet Of Things written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Building Scalable Edge AI Solutions for the Internet of Things" explores the convergence of IoT, edge computing, and AI, providing a practical guide to developing and deploying intelligent edge solutions. The book begins by establishing foundational concepts, explaining the limitations of cloud-centric IoT architectures and introducing the benefits of edge computing and Edge AI, such as reduced latency, bandwidth efficiency, and enhanced privacy. It then delves into the building blocks of Edge AI solutions, covering data acquisition and preprocessing techniques optimized for resource-constrained devices, model selection and compression strategies, and an overview of relevant frameworks and hardware platforms like MCUs, MPUs, GPUs, and FPGAs. The book further provides a practical development approach, detailing the steps from problem definition and data preparation to model training, evaluation, and deployment on edge devices. It emphasizes the importance of robust deployment strategies, including OTA updates, device management tools, and crucial security considerations. Finally, the book examines advanced topics like real-time Edge AI applications in industrial automation, robotics, and autonomous systems, along with scalability and orchestration strategies for large deployments. It concludes by exploring future trends, including emerging hardware and software, the role of 5G, and the ethical implications of Edge AI, advocating for responsible AI development.
Advanced Fractal Graph Theory And Applications
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Author : P. Tharaniya
language : en
Publisher: CRC Press
Release Date : 2024-12-30
Advanced Fractal Graph Theory And Applications written by P. Tharaniya and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Mathematics categories.
This book explores the dynamic interplay between fractals and graph theory, two powerful mathematical tools with vast applications. It presents a strategic combination and the synergistic use of these disciplines to address real-world problems and challenges. The book begins with an introduction to the basic concepts of fractals and graph theory and goes on to explore the applications in various domains, including natural phenomena modeling, scheduling, and network optimisation. This book: Illustrates the innovative ways fractals and graph theory can be combined, laying the groundwork for future applications across various industries Introduces the fundamental concepts and principles of both fractals and graph theory in detail, making it accessible to a broad audience, including those new to these topics Explores practical applications in image processing, network optimisation, social network analysis, and more, demonstrating the real-world impact of these mathematical tools Analyses advanced techniques in graph theory, such as matching, domination, and colouring, with practical examples and case studies Highlights the latest research advancements in fractal graph theory, showcasing its potential for future developments and applications This book is for students, researchers, and professionals in mathematics, computer science, engineering, and related fields.
Deep Learning With Azure
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Author : Mathew Salvaris
language : en
Publisher:
Release Date : 2018
Deep Learning With Azure written by Mathew Salvaris and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Microsoft Azure (Computing platform) categories.
Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI?Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll LearnBecome familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AIUse pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more)Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolvingDiscover the options for training and operationalizing deep learning models on Azure Who This Book Is ForProfessional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.
Human Centric Integration Of 6g Enabled Technologies For Modern Society
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Author : Amit Kumar Tyagi
language : en
Publisher: Elsevier
Release Date : 2025-04-29
Human Centric Integration Of 6g Enabled Technologies For Modern Society written by Amit Kumar Tyagi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-29 with Science categories.
Human-Centric Integration of 6G-Enabled Technologies for Modern Society: Fundamentals, Applications, Analysis and Challenges serves as a comprehensive reference, addressing the information needs of professionals by providing deep information about the fundamentals and applications of 6G, enabling them to make informed decisions in the dynamic landscape of advanced communication technologies. In the 23 chapters, this book introduces the reader to the 6G technology, the evolution of wireless communication, and the integration of artificial intelligence; provides the use cases and applications of 6G technology and the insights into the challenges, future trends, and emerging technologies; and includes the applications of 6G technology in remote healthcare services, patient monitoring, and medical diagnostics.Human-Centric Integration of 6G-Enabled Technologies for Modern Society: Fundamentals, Applications, Analysis and Challenges redefines the way we connect, communicate, and collaborate with emerging technologies in this smart era of 6G technology. The title benefits from a collective wealth of knowledge and perspectives. This diversity enriches the content, providing readers with insights from various angles, setting it apart from publications authored or edited by a limited number of individuals. - It discusses both the like fundamental concepts, diverse applications and analytical methodologies, as the challenges that come with the development and deployment of 6G-enabled technologies - It is designed to address the latest developments in 6G technology, offering a forward-looking perspective on emerging trends - It ensures that readers receive up-to-date information and insights into the rapidly evolving landscape of next-generation wireless communication
Sagemaker Essentials
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-05-31
Sagemaker Essentials written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-31 with Computers categories.
"SageMaker Essentials" "SageMaker Essentials" offers a comprehensive guide to mastering Amazon SageMaker, the leading platform for machine learning at scale. This authoritative resource meticulously explores the platform’s architecture, seamlessly guiding readers through elastic infrastructure management, secure data integration, CI/CD pipeline integration, and best practices for leveraging SageMaker Studio and modern SDKs. Emphasizing enterprise needs, the book provides strategies for cost optimization, robust access management, and sustainable machine learning solutions, making it indispensable for organizations seeking operational efficiency in cloud-based AI deployments. With a keen focus on advanced data preparation, readers learn how to automate data wrangling, engineer reusable transformation pipelines, and proactively monitor data quality and drift. The book also delves into complex model training scenarios, such as distributed and multi-node training, hyperparameter optimization, and interactive experimentation, all while maintaining strict budgeting and resource usage control. The end-to-end lifecycle of machine learning, from data processing and labeling with Ground Truth to robust deployment strategies—including real-time, batch, and serverless inference—is covered with practical patterns and production-targeted guidance. Equipped for the demands of modern MLOps, "SageMaker Essentials" details the automation of ML pipelines, advanced monitoring and observability with CloudWatch, and compliance-driven security, governance, and auditability frameworks. Readers will benefit from chapters on hybrid architectures, event-driven workflows, federated learning, and extensibility with open-source and SaaS integrations. Detailed coverage of incident detection, automated remediation, and cost and environmental considerations round out this essential reference for data scientists, ML engineers, architects, and technology leaders committed to scaling secure, compliant, and efficient AI systems on AWS.
Deep Learning
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Author : Li Deng
language : en
Publisher:
Release Date : 2014
Deep Learning written by Li Deng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Machine learning categories.
Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks
Solutions Architect S Handbook
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Author : Saurabh Shrivastava
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29
Solutions Architect S Handbook written by Saurabh Shrivastava and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Computers categories.
From fundamentals and design patterns to the latest techniques such as generative AI, machine learning and cloud native architecture, gain all you need to be a pro Solutions Architect crafting secure and reliable AWS architecture. Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Hits all the key areas -Rajesh Sheth, VP, Elastic Block Store, AWS Offers the knowledge you need to succeed in the evolving landscape of tech architecture - Luis Lopez Soria, Senior Specialist Solutions Architect, Google A valuable resource for enterprise strategists looking to build resilient applications - Cher Simon, Principal Solutions Architect, AWS Book DescriptionBuild a strong foundation in solution architecture and excel in your career with the Solutions Architect’s Handbook. Authored by seasoned AWS technology leaders Saurabh Shrivastav and Neelanjali Srivastav, this book goes beyond traditional certification guides, offering in-depth insights and advanced techniques to meet the specific needs and challenges of solutions architects today. This edition introduces exciting new features that keep you at the forefront of this evolving field. From large language models and generative AI to deep learning innovations, these cutting-edge advancements are shaping the future of technology. Key topics such as cloud-native architecture, data engineering architecture, cloud optimization, mainframe modernization, and building cost-efficient, secure architectures remain essential today. This book covers both emerging and foundational technologies, guiding you through solution architecture design with key principles and providing the knowledge you need to succeed as a Solutions Architect. It also sharpens your soft skills, providing career-accelerating techniques to stay ahead. By the end of this book, you will be able to harness cutting-edge technologies, apply practical insights from real-world scenarios, and enhance your solution architecture skills with the Solutions Architect's Handbook.What you will learn Explore various roles of a solutions architect in the enterprise Apply design principles for high-performance, cost-effective solutions Choose the best strategies to secure your architectures and boost availability Develop a DevOps and CloudOps mindset for collaboration, operational efficiency, and streamlined production Apply machine learning, data engineering, LLMs, and generative AI for improved security and performance Modernize legacy systems into cloud-native architectures with proven real-world strategies Master key solutions architect soft skills Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders who already work in the IT industry and aspire to become solutions architect professionals. Solutions architects who want to expand their skillset or get a better understanding of new technologies will also learn valuable new skills. To get started, you'll need a good understanding of the real-world software development process and some awareness of cloud technology.
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.
Building Machine Learning And Deep Learning Models On Google Cloud Platform
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Author : Ekaba Bisong
language : en
Publisher:
Release Date : 2019
Building Machine Learning And Deep Learning Models On Google Cloud Platform written by Ekaba Bisong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Cloud computing categories.
Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. You will: Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your results Know the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products.