"The overall aim of the book is to extend recent concepts, methodologies, and empirical research advances of various biological data mining systems through machine learning approaches. Covering a diverse set of research in these areas, this publication is ideally designed for use by technology development, academicians, data scientists, industrial professionals (inspection specialist), researchers and students interested in uncovering the latest innovations in the field"--
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Dr. U. Vignesh , is currently an Assistant Professor Senior Grade 2 in School of Computer Science and Engineering, Vellore Institute of Technology (VIT) - Chennai. Prior to his recent appointment at the VIT, he was a Post-Doctoral Fellow in National Institute of Technology (NIT), Trichy – India. Dr. Vignesh received his undergraduate degree in B.Tech (IT) as well as his M.Tech (IT) degree from Anna University - Chennai, and his PhD in Computer Science and Engineering from VIT University - Chennai. Dr. Vignesh published several papers in preferred Journals, patents and chapters in books, and participated in a range of forums on computer science, social science, etc. He also presented various academic as well as research-based papers at several national and international conferences. His research activities are currently twofold: while the first research activity is set to explore the developmental role that society needs with technology such as, Artificial Intelligence; the second major research theme that he is pursuing is focused on the bioinformatics and data mining.
R.Parvathi is a Professor of School of Computing Science and Engineering at VIT University, Chennai since 2011. She received the Doctoral degree in the field of spatial data mining in the same year. Her teaching experience in the area of computer science includes more than two decades and her research interests include data mining, big data and computational biology.
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Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
Zustand: New. In. Artikel-Nr. ria9781668465240_new
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