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Data-Centric Artificial Intelligence for Multidisciplinary Applications

Data-Centric Artificial Intelligence for Multidisciplinary Applications
Author: Parikshit N Mahalle
Publisher: CRC Press
Total Pages: 309
Release: 2024-06-06
Genre: Computers
ISBN: 1040031137

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This book explores the need for a data‐centric AI approach and its application in the multidisciplinary domain, compared to a model‐centric approach. It examines the methodologies for data‐centric approaches, the use of data‐centric approaches in different domains, the need for edge AI and how it differs from cloud‐based AI. It discusses the new category of AI technology, "data‐centric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, data‐centric AI modifies this by enabling it to learn from data rather than depending on algorithms. It can therefore make wiser choices and deliver more precise outcomes. Additionally, it has the potential to be significantly more scalable than conventional AI methods. • Includes a collection of case studies with experimentation results to adhere to the practical approaches • Examines challenges in dataset generation, synthetic datasets, analysis, and prediction algorithms in stochastic ways • Discusses methodologies to achieve accurate results by improving the quality of data • Comprises cases in healthcare and agriculture with implementation and impact of quality data in building AI applications


Data Centric Artificial Intelligence: A Beginner’s Guide

Data Centric Artificial Intelligence: A Beginner’s Guide
Author: Parikshit N. Mahalle
Publisher: Springer Nature
Total Pages: 137
Release: 2023-11-11
Genre: Technology & Engineering
ISBN: 9819963532

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This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.


Data-Driven Mining, Learning and Analytics for Secured Smart Cities

Data-Driven Mining, Learning and Analytics for Secured Smart Cities
Author: Chinmay Chakraborty
Publisher: Springer Nature
Total Pages: 383
Release: 2021-04-28
Genre: Computers
ISBN: 3030721396

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This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.


Technologies and Applications for Big Data Value

Technologies and Applications for Big Data Value
Author: Edward Curry
Publisher: Springer Nature
Total Pages: 555
Release: 2022
Genre: Application software
ISBN: 3030783073

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This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.


Advances in Applications of Data-Driven Computing

Advances in Applications of Data-Driven Computing
Author: Jagdish Chand Bansal
Publisher:
Total Pages: 0
Release: 2021
Genre:
ISBN: 9789813369207

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This book aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behaviour of applications. Applications of Artificial intelligence (AI)-based systems play a significant role in today's software industry. The sensors data from hardware-based systems making a mammoth database, increasing day by day. Recent advances in big data generation and management have created an avenue for decision-makers to utilize these huge volumes of data for different purposes and analyses. AI-based application developers have long utilized conventional machine learning techniques to design better user interfaces and vulnerability predictions. However, with the advancement of deep learning-based and neural-based networks and algorithms, researchers are able to explore and learn more about data and their exposed relationships or hidden features. This new trend of developing data-driven application systems seeks the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cyber security, human activity recognition, and behavioural modelling. As such, computational neural networks algorithms can be refined to address problems in data-driven applications. Original research and review works with model and build data-driven applications using computational algorithm are included as chapters in this book. .


Innovations in Artificial Intelligence and Human-Computer Interaction in the Digital Era

Innovations in Artificial Intelligence and Human-Computer Interaction in the Digital Era
Author: Surbhi Bhatia Khan
Publisher: Elsevier
Total Pages: 342
Release: 2023-07-22
Genre: Computers
ISBN: 0323999492

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Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like “Wizard of Oz prototyping and “Thinking aloud protocols. Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains. Presents fundamental concepts of both HCI and AI, addressing a multidisciplinary audience of researchers and engineers working on User Centered Design (UCD), User Interface (UI) design, and User Experience (UX) design Explores a broad range of case studies from across healthcare, industry, and education Investigates multiple strategies for designing and developing intelligent user interfaces to solve real-world problems Outlines research challenges and future directions for the intersection of AI and HCI


Data-Driven Innovation for Intelligent Technology

Data-Driven Innovation for Intelligent Technology
Author: Hiram Ponce
Publisher: Springer
Total Pages: 0
Release: 2024-04-28
Genre: Computers
ISBN: 9783031542763

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​ This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value. It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others. This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems.


Information Technology in Organisations and Societies

Information Technology in Organisations and Societies
Author: Zach W. Y. Lee
Publisher: Emerald Group Publishing
Total Pages: 269
Release: 2021-06-11
Genre: Business & Economics
ISBN: 1839098120

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Information Technology in Organisations and Societies: Multidisciplinary Perspectives from AI to Technostress consolidates studies on key issues and phenomena concerning the positive and negative aspects of IT use as well as prescribing future research avenues in related research.