Download or read book Federated AI for Real World Business Scenarios written by Dinesh C. Verma and published by CRC Press. This book was released on 2021-10-01 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of Federated Learning and how it can be used to build real-world AI-enabled applications. Real-world AI applications frequently have training data distributed in many different locations, with data at different sites having different properties and different formats. In many cases, data movement is not permitted due to security concerns, bandwidth, cost or regulatory restriction. Under these conditions, techniques of federated learning can enable creation of practical applications. Creating practical applications requires implementation of the cycle of learning from data, inferring from data, and acting based on the inference. This book will be the first one to cover all stages of the Learn-Infer-Act cycle, and presents a set of patterns to apply federation to all stages. Another distinct feature of the book is the use of real-world applications with an approach that discusses all aspects that need to be considered in an operational system, including handling of data issues during federation, maintaining compliance with enterprise security policies, and simplifying the logistics of federated AI in enterprise contexts. The book considers federation from a manner agnostic to the actual AI models, allowing the concepts to be applied to all varieties of AI models. This book is probably the first one to cover the space of enterprise AI-based applications in a holistic manner.

Download or read book Federated AI for Real World Business Scenarios written by Dinesh C. Verma and published by CRC Press. This book was released on 2021-10-01 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of Federated Learning and how it can be used to build real-world AI-enabled applications. Real-world AI applications frequently have training data distributed in many different locations, with data at different sites having different properties and different formats. In many cases, data movement is not permitted due to security concerns, bandwidth, cost or regulatory restriction. Under these conditions, techniques of federated learning can enable creation of practical applications. Creating practical applications requires implementation of the cycle of learning from data, inferring from data, and acting based on the inference. This book will be the first one to cover all stages of the Learn-Infer-Act cycle, and presents a set of patterns to apply federation to all stages. Another distinct feature of the book is the use of real-world applications with an approach that discusses all aspects that need to be considered in an operational system, including handling of data issues during federation, maintaining compliance with enterprise security policies, and simplifying the logistics of federated AI in enterprise contexts. The book considers federation from a manner agnostic to the actual AI models, allowing the concepts to be applied to all varieties of AI models. This book is probably the first one to cover the space of enterprise AI-based applications in a holistic manner.

Download or read book Federated Learning with Python written by Kiyoshi Nakayama PhD and published by Packt Publishing Ltd. This book was released on 2022-10-28 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the essential skills for building an authentic federated learning system with Python and take your machine learning applications to the next level Key FeaturesDesign distributed systems that can be applied to real-world federated learning applications at scaleDiscover multiple aggregation schemes applicable to various ML settings and applicationsDevelop a federated learning system that can be tested in distributed machine learning settingsBook Description Federated learning (FL) is a paradigm-shifting technology in AI that enables and accelerates machine learning (ML), allowing you to work on private data. It has become a must-have solution for most enterprise industries, making it a critical part of your learning journey. This book helps you get to grips with the building blocks of FL and how the systems work and interact with each other using solid coding examples. FL is more than just aggregating collected ML models and bringing them back to the distributed agents. This book teaches you about all the essential basics of FL and shows you how to design distributed systems and learning mechanisms carefully so as to synchronize the dispersed learning processes and synthesize the locally trained ML models in a consistent manner. This way, you'll be able to create a sustainable and resilient FL system that can constantly function in real-world operations. This book goes further than simply outlining FL's conceptual framework or theory, as is the case with the majority of research-related literature. By the end of this book, you'll have an in-depth understanding of the FL system design and implementation basics and be able to create an FL system and applications that can be deployed to various local and cloud environments. What you will learnDiscover the challenges related to centralized big data ML that we currently face along with their solutionsUnderstand the theoretical and conceptual basics of FLAcquire design and architecting skills to build an FL systemExplore the actual implementation of FL servers and clientsFind out how to integrate FL into your own ML applicationUnderstand various aggregation mechanisms for diverse ML scenariosDiscover popular use cases and future trends in FLWho this book is for This book is for machine learning engineers, data scientists, and artificial intelligence (AI) enthusiasts who want to learn about creating machine learning applications empowered by federated learning. You'll need basic knowledge of Python programming and machine learning concepts to get started with this book.

Download or read book Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment Big Data Modeling and Simulation written by Kothe Doug and published by Springer Nature. This book was released on 2023-01-17 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd Smoky Mountains Computational Sciences and Engineering Conference on Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, SMC 2022, held virtually, during August 23–25, 2022. The 24 full papers included in this book were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows: foundational methods enabling science in an integrated ecosystem; science and engineering applications requiring and motivating an integrated ecosystem; systems and software advances enabling an integrated science and engineering ecosystem; deploying advanced technologies for an integrated science and engineering ecosystem; and scientific data challenges.

Download or read book Re imagining Diffusion and Adoption of Information Technology and Systems A Continuing Conversation written by Sujeet K. Sharma and published by Springer Nature. This book was released on 2020-12-15 with total page 733 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of IFIP AICT 617 and 618 constitutes the refereed proceedings of the IFIP WG 8.6 International Working Conference "Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation" on Transfer and Diffusion of IT, TDIT 2020, held in Tiruchirappalli, India, in December 2020. The 86 revised full papers and 36 short papers presented were carefully reviewed and selected from 224 submissions. The papers focus on the re-imagination of diffusion and adoption of emerging technologies. They are organized in the following parts: Part I: artificial intelligence and autonomous systems; big data and analytics; blockchain; diffusion and adoption technology; emerging technologies in e-Governance; emerging technologies in consumer decision making and choice; fin-tech applications; healthcare information technology; and Internet of Things Part II: information technology and disaster management; adoption of mobile and platform-based applications; smart cities and digital government; social media; and diffusion of information technology and systems

Download or read book Advancing Software Engineering Through AI Federated Learning and Large Language Models written by Sharma, Avinash Kumar and published by IGI Global. This book was released on 2024-05-02 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics.

Download or read book AI Blueprints written by Dr. Joshua Eckroth and published by Packt Publishing Ltd. This book was released on 2018-12-31 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential blueprints and workflow you need to build successful AI business applications Key FeaturesLearn and master the essential blueprints to program AI for real-world business applicationsGain insights into how modern AI and machine learning solve core business challengesAcquire practical techniques and a workflow that can build AI applications using state-of-the-art software librariesWork with a practical, code-based strategy for creating successful AI solutions in your businessBook Description AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You’ll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you’ll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You’ll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a ‘trending now’ section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers’ questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you’ll also learn how to prepare for future advances in AI. You’ll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code. What you will learnAn essential toolbox of blueprints and advanced techniques for building AI business applicationsHow to design and deploy AI applications that meet today’s business needsA workflow from first design stages to practical code solutions in your next AI projectsSolutions for AI projects that involve social media analytics and recommendation enginesPractical projects and techniques for sentiment analysis and helpful chatbotsA blueprint for AI projects that recommend products based on customer purchasing habitsHow to prepare yourself for the next decade of AI and machine learning advancementsWho this book is for Programming AI Business Applications provides an introduction to AI with real-world examples. This book can be read and understood by programmers and students without requiring previous AI experience. The projects in this book make use of Java and Python and several popular and state-of-the-art opensource AI libraries.

Download or read book Artificial Intelligence and Machine Learning for Open world Novelty written by and published by Elsevier. This book was released on 2024-02-20 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Computers, Volume presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on - Contains novel subject matter that is relevant to computer science - Includes the expertise of contributing authors - Presents an easy to comprehend writing style

Download or read book Service Oriented Computing ICSOC 2023 Workshops written by Flavia Monti and published by Springer Nature. This book was released on with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Artificial Intelligence for Entrepreneurs written by Jamie Flux and published by Independently Published. This book was released on 2024-08-11 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the endless possibilities of Artificial Intelligence (AI). This comprehensive book covers a wide range of industries, including retail, healthcare, finance, education, manufacturing, transportation, agriculture, and more. Key Features: - In-depth exploration of AI applications in various sectors - Python code examples to enhance understanding and implementation - Real-world use cases to inspire your own business ideas - Insights from industry experts to guide your AI strategy Book Description: Artificial Intelligence is transforming businesses across the globe, and now you have the opportunity to harness its power. In this book, you'll dive into the world of AI and explore its widespread applications in different industries. Each chapter focuses on a specific field, offering a comprehensive analysis of how AI is revolutionizing processes, improving efficiency, and transforming customer experiences. What You Will Learn: - Understand the AI applications in various industries such as retail, healthcare, finance, education, manufacturing, transportation, and more - Explore practical use cases and real-world examples of AI implementation - Gain insights into the Python code used in AI applications - Develop a strong understanding of AI-driven technologies like machine learning, natural language processing, and robotics - Master the techniques for designing AI solutions tailored to specific industries Whether you're a seasoned entrepreneur looking to expand your business or a startup founder seeking innovative solutions, this book is for you. No prior AI knowledge is required, as this book provides a comprehensive introduction to AI concepts and methodologies. Leverage the power of AI to transform your business and stay ahead of the game.

Download or read book The Neural Economy written by Suncre O Marquis and published by Independently Published. This book was released on 2024-03-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The Neural Economy" is a compelling exploration into the seismic shifts occurring in the global business landscape, driven by the unstoppable force of artificial intelligence (AI). This book offers a panoramic view of AI's disruptive power, transforming how we work, innovate, and compete. As AI reshapes industries from healthcare to finance, manufacturing to retail, readers will discover not only the immense opportunities but also the challenges that accompany this digital revolution. Authored by a leading expert in the field of technology and innovation, this book demystifies the intricate workings of AI, from neural networks to machine learning algorithms, and elucidates their applications in real-world business scenarios. Through captivating case studies, "The Neural Economy" showcases businesses at the cutting edge of AI integration, revealing the strategies behind their success and the lessons learned along the way. More than just a technological overview, this book delves into the profound economic implications of AI, examining its impact on job markets, privacy, and ethical considerations. It provides a balanced perspective, acknowledging the potential for AI to exacerbate inequalities and the importance of navigating these advancements with foresight and responsibility. "The Neural Economy" is an indispensable guide for business leaders, policymakers, and enthusiasts eager to understand the future of business in an AI-dominated world. It offers actionable insights for leveraging AI to drive growth and innovation, preparing readers to navigate the uncertainties of the neural economy with confidence. This book is not just about surviving the AI revolution but thriving in the new era it heralds. Join the journey into the heart of tomorrow's business world, and be part of shaping a future where technology and humanity converge for the greater good.

Download or read book Autonomous Driving Network written by Wenshuan Dang and published by CRC Press. This book was released on 2024-01-17 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aiming to outline the vision of realizing automated and intelligent communication networks in the era of intelligence, this book describes the development history, application scenarios, theories, architectures, and key technologies of Huawei's Autonomous Driving Network (ADN) solution. In the book, the authors explain the design of the top-level architecture, hierarchical architecture (ANE, NetGraph, and AI Native NE), and key feature architecture (distributed AI and endogenous security) that underpin Huawei's ADN solution. The book delves into various key technologies, including trustworthy AI, distributed AI, digital twin, network simulation, digitization of knowledge and expertise, human-machine symbiosis, NE endogenous intelligence, and endogenous security. It also provides an overview of the standards and level evaluation methods defined by industry and standards organizations, and uses Huawei's ADN solution as an example to illustrate how to implement AN. This book is an essential reference for professionals and researchers who want to gain a deeper understanding of automated and intelligent communication networks and their applications.

Download or read book Beyond Algorithms written by James Luke and published by CRC Press. This book was released on 2022-05-29 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on the definition, engineering, and delivery of AI solutions as opposed to AI itself Reader will still gain a strong understanding of AI, but through the perspective of delivering real solutions Explores the core AI issues that impact the success of an overall solution including i. realities of dealing with data, ii. impact of AI accuracy on the ability of the solution to meet business objectives, iii. challenges in managing the quality of machine learning models Includes real world examples of enterprise scale solutions Provides a series of (optional) technical deep dives and thought experiments.

Download or read book Federated Learning written by Qiang Yang and published by Springer Nature. This book was released on 2020-11-25 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and self-contained introduction to federated learning, ranging from the basic knowledge and theories to various key applications. Privacy and incentive issues are the focus of this book. It is timely as federated learning is becoming popular after the release of the General Data Protection Regulation (GDPR). Since federated learning aims to enable a machine model to be collaboratively trained without each party exposing private data to others. This setting adheres to regulatory requirements of data privacy protection such as GDPR. This book contains three main parts. Firstly, it introduces different privacy-preserving methods for protecting a federated learning model against different types of attacks such as data leakage and/or data poisoning. Secondly, the book presents incentive mechanisms which aim to encourage individuals to participate in the federated learning ecosystems. Last but not least, this book also describes how federated learning can be applied in industry and business to address data silo and privacy-preserving problems. The book is intended for readers from both the academia and the industry, who would like to learn about federated learning, practice its implementation, and apply it in their own business. Readers are expected to have some basic understanding of linear algebra, calculus, and neural network. Additionally, domain knowledge in FinTech and marketing would be helpful.”

Download or read book AI 2041 written by Kai-Fu Lee and published by Crown Currency. This book was released on 2024-03-05 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: How will AI change our world within twenty years? A pioneering technologist and acclaimed writer team up for a “dazzling” (The New York Times) look at the future that “brims with intriguing insights” (Financial Times). This edition includes a new foreword by Kai-Fu Lee. A BEST BOOK OF THE YEAR: The Wall Street Journal, The Washington Post, Financial Times Long before the advent of ChatGPT, Kai-Fu Lee and Chen Qiufan understood the enormous potential of artificial intelligence to transform our daily lives. But even as the world wakes up to the power of AI, many of us still fail to grasp the big picture. Chatbots and large language models are only the beginning. In this “inspired collaboration” (The Wall Street Journal), Lee and Chen join forces to imagine our world in 2041 and how it will be shaped by AI. In ten gripping, globe-spanning short stories and accompanying commentary, their book introduces readers to an array of eye-opening settings and characters grappling with the new abundance and potential harms of AI technologies like deep learning, mixed reality, robotics, artificial general intelligence, and autonomous weapons.

Download or read book Privacy preserving Computing written by Kai Chen and published by Cambridge University Press. This book was released on 2023-11-30 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematically introduces privacy-preserving computing techniques and practical applications for students, researchers, and practitioners.

Download or read book Mobile Edge Computing written by Yan Zhang and published by Springer Nature. This book was released on 2021-10-01 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks.The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management.The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists.