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A vital book by industry thought leader and global AI expert, Dr. Lance Eliot, and based on his popular AI Insider series and podcasts, this fascinating book provides pioneering advances and momentum for the advent of AI self-driving driverless autonomous cars. Included too are keen insights about the practical application of Artificial Intelligence (AI) and Machines Learning (ML).
A vital book by industry thought leader and global AI expert, Dr. Lance Eliot, and based on his popular AI Insider series and podcasts, this fascinating book provides pioneering advances and momentum for the advent of AI self-driving driverless autonomous cars. Included too are keen insights about the practical application of Artificial Intelligence (AI) and Machines Learning (ML).
The increase in smartphone usage and new technologies embedded in smart devices have led to innovative developments and applications throughout a variety of industries. However, new techniques such as spatial augmented reality are becoming more affordable for business, allowing consumers to experience and interact with the world as they never have before. AR and VR have vast implications for management and can allow companies to increase their sustainability and reduce their CO2 footprint. Managerial Challenges and Social Impacts of Virtual and Augmented Reality is a pivotal reference source that provides vital research on the applications of VR, AR, and related technologies from the perspectives of managers and marketers in the industry and discusses the social impact of these technologies. While highlighting topics such as consumer analysis, privacy ethics, and relationship marketing, this book is ideally designed for managers, marketers, technology developers, managing directors, business professionals, academicians, students, and researchers seeking current studies on the evolution of interactive technology.
Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.
The subject of Artificial Intelligence (AI) is continuing on its journey of affecting each and every individual and will keep on this path in the times to come. This handbook is a collection of topics on the application of artificial intelligence applications for sustainability in different areas. It provides an insight into the various uses of concepts and practical examples for different domains all in one place, which makes it unique and important for the potential reader. Handbook of Artificial Intelligence Applications for Industrial Sustainability: Concepts and Practical Examples examines the influence of AI and how it can be used in several industries to improve corporate performance, reduce security concerns, improve customer experience, and ultimately generate value for customers and maximize profits. The handbook offers practical examples, concepts, and applications that provide an easy understanding and implementation process. It provides AI applications in many fields, such as sustainable credit decisions, cyber security and fraud prevention, warehouse management, and much more. This handbook will provide insight to customers, managers, professionals, engineers, researchers, and students on the various uses of AI and sustainability in different domains. All of this needed information compiled into one handbook makes it unique and important for the engineering, business, and computer science communities.
This book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of Artificial Intelligence. The book provides a premier interdisciplinary platform to present practical challenges and adopted solutions. The book addresses the complete functional framework workflow in Artificial Intelligence technology. It explores the basic and high-level concepts and can serve as a manual for the industry for beginners and the more advanced. It covers intelligent and automated systems and its implications to the real-world, and offers data acquisition and case studies related to data-intensive technologies in AI-based applications. The book will be of interest to researchers, professionals, scientists, professors, students of computer science engineering, electronics and communications, as well as information technology.
This book dives deep into the crucial intersection of business and technology, two forces shaping our world. It's a practical guide for executives, business owners, and anyone who wants to understand how technology is transforming industries and corporate strategies. With this book you can discover the real impact of technology, business-technology convergence, adapting to change, practical insights and unveil the intricacies. Don't be left behind. "The Convergence of Business and Technology" equips you with the knowledge and tools you need to thrive in this rapidly evolving digital age.
Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.