Advances in Partitioning Techniques - Guggari, Shankru; V, Umadevi; Kadappa, Vijayakumar
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Erscheint vorauss. 2. Juni 2025
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The book discusses various partitioning strategies tailored for traditional machine learning algorithms. This book is a vital resource, illuminating the path towards unlocking the full potential of partitioning in shaping the future of AI technologies.

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Produktbeschreibung
The book discusses various partitioning strategies tailored for traditional machine learning algorithms. This book is a vital resource, illuminating the path towards unlocking the full potential of partitioning in shaping the future of AI technologies.
Autorenporträt
Shankru 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.