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OverviewFull Product DetailsAuthor: Shankru Guggari , Umadevi V , Vijayakumar KadappaPublisher: Taylor & Francis Ltd Imprint: Chapman & Hall/CRC Weight: 0.410kg ISBN: 9781032750019ISBN 10: 1032750014 Pages: 122 Publication Date: 01 June 2025 Audience: College/higher education , Professional and scholarly , Tertiary & Higher Education , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1. Introduction to Partitioning Techniques 2. Partitioning Techniques for Deep Learning techniques 3. Graph based partitioning techniques 4. Partitioning techniques for Bigdata 5. Partitioning techniques for edge ComputingReviewsAuthor InformationShankru Guggari is a machine learning specialist who primarily focuses on enhancing the performance of machine learning techniques. His research interests include pattern recognition, explainable AI, and machine learning. He has published his work in various international conferences and journals and has over four years of academic experience. Umadevi V, PhD from IIT Madras, is a Professor of Computer Science at BMS College of Engineering, Bangalore and a Senior IEEE member. She has published extensively in reputed journals and conferences and received grants for research in medical thermography. Vijaya Kumar Kadappa obtained his PhD in from the Central University of Hyderabad in 2010 and working as Professor at the Department of Computer Applications, BMS College of Engineering, Bangalore. He has 30+ research publications. Kadappa is a life member of IUPR-AI, ISTE, and CSI. Tab Content 6Author Website:Countries AvailableAll regions |