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Edge Computing Machine Learning A Complete Guide 2020 Edition
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Book Synopsis Edge Computing Machine Learning A Complete Guide - 2020 Edition by : Gerardus Blokdyk
Download or read book Edge Computing Machine Learning A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edge Computing Machine Learning A Complete Guide - 2020 Edition.
Book Synopsis Edge Computing Machine Learning A Complete Guide - 2020 Edition by : Gerardus Blokdyk
Download or read book Edge Computing Machine Learning A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-09-23 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: What will drive edge computing machine learning change? Who will provide the final approval of edge computing machine learning deliverables? Is the impact that edge computing machine learning has shown? How does your organization evaluate strategic edge computing machine learning success? How do you assess your edge computing machine learning workforce capability and capacity needs, including skills, competencies, and staffing levels? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Edge Computing Machine Learning investments work better. This Edge Computing Machine Learning All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Edge Computing Machine Learning Self-Assessment. Featuring 955 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Edge Computing Machine Learning improvements can be made. In using the questions you will be better able to: - diagnose Edge Computing Machine Learning projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Edge Computing Machine Learning and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Edge Computing Machine Learning Scorecard, you will develop a clear picture of which Edge Computing Machine Learning areas need attention. Your purchase includes access details to the Edge Computing Machine Learning self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Edge Computing Machine Learning Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Book Synopsis Deep Learning and Edge Computing Solutions for High Performance Computing by : A. Suresh
Download or read book Deep Learning and Edge Computing Solutions for High Performance Computing written by A. Suresh and published by Springer Nature. This book was released on 2021-01-27 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an insight into ways of inculcating the need for applying mobile edge data analytics in bioinformatics and medicine. The book is a comprehensive reference that provides an overview of the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to the healthcare field. Topics include deep learning methods for applications in object detection and identification, object tracking, human action recognition, and cross-modal and multimodal data analysis. High performance computing systems for applications in healthcare are also discussed. The contributors also include information on microarray data analysis, sequence analysis, genomics based analytics, disease network analysis, and techniques for big data Analytics and health information technology.
Book Synopsis Machine Learning for Edge Computing by : Amitoj Singh
Download or read book Machine Learning for Edge Computing written by Amitoj Singh and published by CRC Press. This book was released on 2022-07-29 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Edge Computing A Complete Guide - 2021 Edition by : Gerardus Blokdyk
Download or read book Edge Computing A Complete Guide - 2021 Edition written by Gerardus Blokdyk and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Intelligence for Cloud and Edge Computing by : Sanjay Misra
Download or read book Artificial Intelligence for Cloud and Edge Computing written by Sanjay Misra and published by Springer Nature. This book was released on 2022-01-13 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the future possibilities of AI with cloud computing and edge computing. The main goal of this book is to conduct analyses, implementation and discussion of many tools (of artificial intelligence, machine learning and deep learning and cloud computing, fog computing, and edge computing including concepts of cyber security) for understanding integration of these technologies. With this book, readers can quickly get an overview of these emerging topics and get many ideas of the future of AI with cloud, edge, and in many other areas. Topics include machine and deep learning techniques for Internet of Things based cloud systems; security, privacy and trust issues in AI based cloud and IoT based cloud systems; AI for smart data storage in cloud-based IoT; blockchain based solutions for AI based cloud and IoT based cloud systems.This book is relevent to researchers, academics, students, and professionals.
Book Synopsis Edge Computing by : K. Anitha Kumari
Download or read book Edge Computing written by K. Anitha Kumari and published by CRC Press. This book was released on 2021-12-22 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reference text presents the state-of-the-art in edge computing, its primitives, devices and simulators, applications, and healthcare-based case studies. The text provides integration of blockchain with edge computing systems and integration of edge with Internet of Things (IoT) and cloud computing. It will facilitate readers to setup edge-based environment and work with edge analytics. It covers important topics, including cluster computing, fog computing, networking architecture, edge computing simulators, edge analytics, privacy-preserving schemes, edge computing with blockchain, autonomous vehicles, and cross-domain authentication. Aimed at senior undergraduate, graduate students and professionals in the fields of electrical engineering, electronics engineering, computer science, and information technology, this text: Discusses edge data storage security with case studies and blockchain integration with the edge computing system Covers theoretical methods with the help of applications, use cases, case studies, and examples Provides healthcare real-time case studies elaborated by utilizing the virtues of homomorphic encryption Discusses real-time interfaces, devices, and simulators in detail
Book Synopsis Empowered Edge Computing A Complete Guide - 2020 Edition by : Gerardus Blokdyk
Download or read book Empowered Edge Computing A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2020-01-28 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why is edge computing growing and what are the impacts on industrial/factory applications? Is the functionality of edge micro-services equivalent across different carriers? How will fixed networks and business models be impacted? How to relate network metrics to quality of immersion? Do you find Edge Computing architecture in Open Source? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Empowered Edge Computing investments work better. This Empowered Edge Computing All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Empowered Edge Computing Self-Assessment. Featuring 2211 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Empowered Edge Computing improvements can be made. In using the questions you will be better able to: - diagnose Empowered Edge Computing projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Empowered Edge Computing and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Empowered Edge Computing Scorecard, you will develop a clear picture of which Empowered Edge Computing areas need attention. Your purchase includes access details to the Empowered Edge Computing self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Empowered Edge Computing Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Book Synopsis Artificial Intelligence and Machine Learning for EDGE Computing by : Rajiv Pandey
Download or read book Artificial Intelligence and Machine Learning for EDGE Computing written by Rajiv Pandey and published by Elsevier. This book was released on 2022-04-26 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Machine Learning for Predictive and Analytical Rendering in Edge Computing focuses on the role of AI and machine learning as it impacts and works alongside Edge Computing. Sections cover the growing number of devices and applications in diversified domains of industry, including gaming, speech recognition, medical diagnostics, robotics and computer vision and how they are being driven by Big Data, Artificial Intelligence, Machine Learning and distributed computing, may it be Cloud Computing or the evolving Fog and Edge Computing paradigms. Challenges covered include remote storage and computing, bandwidth overload due to transportation of data from End nodes to Cloud leading in latency issues, security issues in transporting sensitive medical and financial information across larger gaps in points of data generation and computing, as well as design features of Edge nodes to store and run AI/ML algorithms for effective rendering. Provides a reference handbook on the evolution of distributed systems, including Cloud, Fog and Edge Computing Integrates the various Artificial Intelligence and Machine Learning techniques for effective predictions at Edge rather than Cloud or remote Data Centers Provides insight into the features and constraints in Edge Computing and storage, including hardware constraints and the technological/architectural developments that shall overcome those constraints
Book Synopsis Edge Computing Architecture A Complete Guide - 2020 Edition by : Gerardus Blokdyk
Download or read book Edge Computing Architecture A Complete Guide - 2020 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-11-17 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: What are the operational costs after edge computing architecture deployment? What is the edge computing architecture's sustainability risk? What is the edge computing architecture Driver? What is edge computing architecture risk? Is the edge computing architecture solution sustainable? This breakthrough Edge Computing Architecture self-assessment will make you the entrusted Edge Computing Architecture domain standout by revealing just what you need to know to be fluent and ready for any Edge Computing Architecture challenge. How do I reduce the effort in the Edge Computing Architecture work to be done to get problems solved? How can I ensure that plans of action include every Edge Computing Architecture task and that every Edge Computing Architecture outcome is in place? How will I save time investigating strategic and tactical options and ensuring Edge Computing Architecture costs are low? How can I deliver tailored Edge Computing Architecture advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Edge Computing Architecture essentials are covered, from every angle: the Edge Computing Architecture self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Edge Computing Architecture outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Edge Computing Architecture practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Edge Computing Architecture are maximized with professional results. Your purchase includes access details to the Edge Computing Architecture self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Edge Computing Architecture Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Book Synopsis Deep Learning on Edge Computing Devices by : Xichuan Zhou
Download or read book Deep Learning on Edge Computing Devices written by Xichuan Zhou and published by Elsevier. This book was released on 2022-02-02 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including neural networks. The title helps researchers maximize the performance of Edge-deep learning models for mobile computing and other applications by presenting neural network algorithms and hardware design optimization approaches for Edge-deep learning. Applications are introduced in each section, and a comprehensive example, smart surveillance cameras, is presented at the end of the book, integrating innovation in both algorithm and hardware architecture. Structured into three parts, the book covers core concepts, theories and algorithms and architecture optimization. This book provides a solution for researchers looking to maximize the performance of deep learning models on Edge-computing devices through algorithm-hardware co-design. Focuses on hardware architecture and embedded deep learning, including neural networks Brings together neural network algorithm and hardware design optimization approaches to deep learning, alongside real-world applications Considers how Edge computing solves privacy, latency and power consumption concerns related to the use of the Cloud Describes how to maximize the performance of deep learning on Edge-computing devices Presents the latest research on neural network compression coding, deep learning algorithms, chip co-design and intelligent monitoring
Book Synopsis Artificial Intelligence by : Melanie Mitchell
Download or read book Artificial Intelligence written by Melanie Mitchell and published by Farrar, Straus and Giroux. This book was released on 2019-10-15 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Melanie Mitchell separates science fact from science fiction in this sweeping examination of the current state of AI and how it is remaking our world No recent scientific enterprise has proved as alluring, terrifying, and filled with extravagant promise and frustrating setbacks as artificial intelligence. The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it. In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go. Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.
Book Synopsis Edge Computing 101: Novice To Pro by : Rob Botwright
Download or read book Edge Computing 101: Novice To Pro written by Rob Botwright and published by Rob Botwright. This book was released on 101-01-01 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing "Edge Computing 101: Novice to Pro" - your ultimate guide to mastering edge computing from beginner to expert level. This comprehensive book bundle includes four essential volumes packed with expert techniques and practical applications to propel your understanding and proficiency in edge computing. Book 1, "Edge Computing Fundamentals: A Beginner's Guide to Distributed Systems," provides a solid foundation for understanding the core principles of distributed systems. Whether you're new to the field or seeking to reinforce your knowledge, this book equips you with the fundamental concepts necessary to embark on your journey into the world of edge computing. In Book 2, "Edge Computing Architectures: Design Principles and Best Practices," you'll delve deeper into the intricacies of designing effective edge computing architectures. From deployment models to optimization techniques, this volume offers invaluable insights and best practices to help you build robust and scalable edge systems. For those looking to advance their skills, Book 3, "Advanced Edge Computing: Scalability, Security, and Optimization Strategies," explores advanced techniques and strategies for overcoming scalability challenges, enhancing security measures, and optimizing performance in edge environments. With real-world examples and case studies, you'll gain practical expertise to tackle complex issues and achieve optimal outcomes. Finally, Book 4, "Edge Computing in Industry 4.0: Practical Applications and Future Trends," focuses on the practical applications of edge computing across various industries, with a special emphasis on Industry 4.0. Discover how edge computing is transforming manufacturing, healthcare, smart cities, and more, and gain insights into future trends shaping the industry. Whether you're a novice looking to build a strong foundation or a seasoned professional aiming to stay ahead of the curve, "Edge Computing 101: Novice to Pro" has you covered. With its comprehensive coverage, expert guidance, and practical insights, this book bundle is your essential companion for mastering the dynamic world of edge computing. Get your copy today and take your edge computing skills to the next level!
Download or read book Machine Learning written by Steven Alex and published by . This book was released on 2019-11-06 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ ★ Buy the Paperback Version of this Book and Get the Kindle Book version for FREE ★ ★ Machine Learning (Update Edition 2019-2020) this Guide is a branch of artificial intelligence, This Machine Learning Series idea is relatively new. A science that researches machines to acquire new knowledge and new skills and to identify existing knowledge. The best way to understand the potential of machine learning is to explore how people and companies are currently taking advantage of it.If you are one of the almost 400 million people with machine learning worldwide, This book offers a method to Techniques! Not every machine learning model uses the same techniques, so training will depend on your approach. Let's consider a few examples: Psychology of learning Machine learning in practice Reinforcement learning Types of machine learning Learning by reinforcement Types of reinforcement The different types of learning This guidebook is going to take some time to explore machine learning, and what it is all about. There are so many different aspects of machine learning and how to make it work for your needs, and all of it is found in this guidebook. Some of the different topics that you will be able to learn about inside include: Neural networks Historical background Why use neural networks? Tasks of neural networks Deep learning Algorithms Starting with python Basic types of data Get access to free software and data sets so you can try out your very own machine learning software. See how advanced machine learning will impact our world in the future! Scroll Up and Click the Buy Now Button!
Book Synopsis Edge Computing Systems with Kubernetes by : Sergio Méndez
Download or read book Edge Computing Systems with Kubernetes written by Sergio Méndez and published by Packt Publishing Ltd. This book was released on 2022-10-14 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand how to use K3s and k3OS for different use cases and discover best practices for building an edge computing system Key FeaturesA guide to implementing an edge computing environmentReduce latency and costs for real-time applications running at the edgeFind stable and relevant cloud native open source software to complement your edge environmentsBook Description Edge computing is a way of processing information near the source of data instead of processing it on data centers in the cloud. In this way, edge computing can reduce latency when data is processed, improving the user experience on real-time data visualization for your applications. Using K3s, a light-weight Kubernetes and k3OS, a K3s-based Linux distribution along with other open source cloud native technologies, you can build reliable edge computing systems without spending a lot of money. In this book, you will learn how to design edge computing systems with containers and edge devices using sensors, GPS modules, WiFi, LoRa communication and so on. You will also get to grips with different use cases and examples covered in this book, how to solve common use cases for edge computing such as updating your applications using GitOps, reading data from sensors and storing it on SQL and NoSQL databases. Later chapters will show you how to connect hardware to your edge clusters, predict using machine learning, and analyze images with computer vision. All the examples and use cases in this book are designed to run on devices using 64-bit ARM processors, using Raspberry Pi devices as an example. By the end of this book, you will be able to use the content of these chapters as small pieces to create your own edge computing system. What you will learnConfigure k3OS and K3s for development and production scenariosPackage applications into K3s for shipped-node scenariosDeploy in occasionally connected scenarios, from one node to one million nodesManage GitOps for applications across different locationsUse open source cloud native software to complement your edge computing systemsImplement observability event-driven and serverless edge applicationsCollect and process data from sensors at the edge and visualize it into the cloudWho this book is for This book is for engineers (developers and/or operators) seeking to bring the cloud native benefits of GitOps and Kubernetes to the edge. Anyone with basic knowledge of Linux and containers looking to learn Kubernetes using examples applied to edge computing and hardware systems will benefit from this book.
Book Synopsis Programming with TensorFlow by : Kolla Bhanu Prakash
Download or read book Programming with TensorFlow written by Kolla Bhanu Prakash and published by Springer Nature. This book was released on 2021-01-22 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics. The book provides a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. The authors begin by working through some basic examples in TensorFlow before diving deeper into topics such as CNN, RNN, LSTM, and GNN. The book is written for those who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. The authors demonstrate TensorFlow projects on Single Board Computers (SBCs).
