Data-Centric Artificial Intelligence for Multidisciplinary Applications (Paperback)
Idioma: inglés
Editorial: Taylor & Francis Ltd, 2026
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- Nuevo

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Paperback. This book explores the need for a datacentric AI approach and its application in the multidisciplinary domain, compared to a modelcentric approach. It examines the methodologies for datacentric approaches, the use of datacentric approaches in different domains, the need for edge AI and how it differs from cloudbased AI. It discusses the new category of AI technology, "datacentric AI" (DCAI), which focuses on comprehending, utilizing, and reaching conclusions from data. By adding machine learning and big data analytics tools, datacentric 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 This book explores the need for a data-centric AI approach and its application in the multidisciplinary domain, compared to a model-centric approach. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…
N° de ref. del artículo 9781032610078
- Título
- Data-Centric Artificial Intelligence for Multidisciplinary Applications (Paperback)
- Autor
- Parikshit N. Mahalle
- Editorial
- Taylor & Francis Ltd
- Año de publicación
- 2026
- Estado
- new
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 10
- 1032610077
- ISBN 13
- 9781032610078
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
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Dr. Parikshit N. Mahalle is a senior member of the IEEE and is Professor and Head of Department of Artificial Intelligence and Data Science at Vishwakarma Institute of Information Technology, Pune, India. He completed his Ph.D. from Aalborg University, Denmark and continued as Post Doc Researcher at CMI, Copenhagen, Denmark. He has 23+ years of teaching and research experience. He is a member of the Board of Studies in Computer Engineering, Ex‑Chairman Information Technology, SPPU and various Universities and autonomous colleges across India. He has 9 patents, 200+ research publications (Google Scholar citations‑2250 plus, H index‑22 and Scopus Citations are 1190 plus with H index ‑16), and authored/edited 42+ books with Springer, CRC Press, Cambridge University Press, etc. He is editor‑in‑chief for IGI Global – International Journal of Rough Sets and Data Analysis, Associate Editor for IGI Global – International Journal of Synthetic Emotions, Inter‑science International Journal of Grid and Utility Computing, member of Editorial Review Board for IGI Global – International Journal of Ambient Computing and Intelligence. His research interests are machine learning, data science, algorithms, internet of things, identity management and security. He is a recognized Ph.D. guide of SSPU, Pune, guiding seven Ph.D. students in the area of IoT and machine learning. Recently, five students have successfully defended their Ph.D. He is also the recipient of the "Best Faculty Award" by Sinhgad Institutes and Cognizant Technologies Solutions. He has delivered 200 plus lectures at national and international levels. He is also the recipient of the best faculty award by Cognizant Technology Solutions.
Dr. Gitanjali R. Shinde is Head and Associate Professor in the Department of Computer Science & Engineering (AI &ML), Vishwakarma Institute of Information Technology, Pune, India. She completed her Ph.D. in Wireless Communication from CMI, Aalborg University, Copenhagen, Denmark on the Research Problem Statement "Cluster Framework for Internet of People, Things and Services" – Ph.D. awarded on 8 May 2018. She earned her M.E. in Computer Engineering from the University of Pune, Pune, in 2012 and B.E. in Computer Engineering degree from the University of Pune, Pune, in 2006. She received research funding for the project "Lightweight group authentication for IoT" by SPPU, Pune. She presented a research article in the World Wireless Research Forum (WWRF) meeting, Beijing, China. She received the best paper award at an international conference. She is also reviewer of various international journals Springer, IGI Global, IEEE Transaction and various conferences. She has published 50+ papers in National and International conferences and journals (Google Scholar citations‑700 plus, H index‑11). She is author of 10+ books with publishers Springer and CRC Press Taylor & Francis Group, and she is also editor of several books. Her book Data Analytics for Pandemics A COVID 19 Case Study was awarded outstanding Book of the year 2020.
Dr. Namrata N. Wasatkar is an Assistant Professor in the Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India. She did her Ph.D. in Computer Engineering from Savitribai Phule Pune University, Pune, India on the research problem statement "Rule based Machine translation of simple Marathi sentences to English sentences" – Ph.D. awarded on 17 November 2022. She earned an M.E. in Computer Engineering from the University of Pune, Pune, in 2014 and B.E. in Computer Engineering from the University of Pune, Pune, in 2012. She has received research funding for the project "SPPU online chatbot" by SPPU, Pune. She is also reviewer for various journals and conferences. She has published 15+ papers in National and International conferences and journals. She has authored a book titled Data Centric Artificial Intelligence: A Beginner’s Guide.
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