Data-Centric Artificial Intelligence for Multidisciplinary Applications

1. Auflage 2024
ISBN: 978-1-03-261006-1
Verlag: Taylor & Francis Ltd

Buch, Englisch, 308 Seiten, Format (B × H): 156 mm x 234 mm

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

Zielgruppe

Academic, Postgraduate, and Professional Reference

Autoren/Hrsg.

R. Shinde, Gitanjali

N Mahalle, Parikshit

Wasatkar, Namrata Nishant

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Datenbankprogrammierung
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Technische Informatik Server

Inhaltsverzeichnis

I) Section I Recent developments in data-centric AI: 1. Advancements in Data-Centric AI Foundations, Ethics, and Emerging Technology 2. Emerging Development and Challenges in Data-Centric AI 3. Unleashing the Power of Industry 4.0: A Harmonious Blend of Data-Centric and Model- Centric AI 4. Data centric AI approaches for machine translation II) Section II Data Centric AI in Healthcare and Agriculture: 5. Case Study Medical Images Analysis and Classification with Data Centric Approach 6. Comparative Analysis of Machine Learning Classification Techniques for Kidney Disease Prediction 7. Fusion of Multi Modal Lumber Spine Scans Using Convolutional Neural Networks 8. Medical Image Analysis and Classification for Varicose Veins 9. Brain Tumor Detection using CNN 10. Explainable Artificial Intelligence in the Healthcare: An Era of Commercialization for AI Solutions 11. Role of Data centric artificial intelligence in agriculture 12. Detection and Classification of Mango Fruit based on Feature extraction applying optimized hybrid LA-FF algorithms III) Section III Building AI with quality Data for multidisciplinary domains: 13 Guiding Your Way: Solving Student Admission Woes 14. Melodic pattern recognition for ornamentation features in music computing 15. Content Analysis Framework for Skill Assessment 16. Machine learning techniques for effective text mining 17. Emails Classification and Anomaly Detection using Natural Language Processing

Über Autor(innen)

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.