Data science revolves around two giants: Big Data analytics and Deep Learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of Big Data as well as Deep Learning systems.
This book discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and decision-making. It also covers numerous applications in healthcare, education, communication, media, and entertainment. Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics offers innovative platforms for integrating Big Data and Deep Learning and presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval.
FEATURES
This book is aimed at industry professionals, academics, research scholars, system modelers, and simulation experts.
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R. Sujatha completed the Ph.D. degree at Vellore Institute of Technology, in 2017 in the area of data mining. She received her M.E. degree in computer science from Anna University in 2009 with university ninth rank and done Master of Financial Management from Pondicherry University in 2005. She received her B.E. degree in computer science from Madras University, in 2001. Has 17 years of teaching experience and has been serving as an associate professor in the School of Information Technology and Engineering in Vellore Institute of Technology, Vellore. Organized and attended a number of workshops and faculty development programs. She actively involves herself in the growth of the institute by contributing to various committees at both academic and administrative levels. She used to guide projects for undergraduate and postgraduate students. Currently guides doctoral students. She gives technical talks in colleges for the symposium and various sessions. She acts as an advisory, editorial member, and technical committee member in conferences conducted in other educational institutions and in-house too. She has published a book titled software project management for college students. Also has published research articles in reputed high impact journals. The institution of Green Engineers awarded IGEN women achiever 2021 in future computing category. Interested to explore different places and visit the same to know about the culture and people of various areas. She is interested in learning upcoming things and gets herself acquainted with the student’s level. Her areas of research interest include Data Mining, Machine Learning, Software Engineering, Soft Computing, Big Data, Deep Learning, and Blockchain.
S. L. Aarthy completed the Ph.D. degree at Vellore Institute of Technology, in 2018 in the area of medical image processing. She received her M.E. degree in computer science from Anna University in 2010. She received her B.E. degree in computer science from Anna University, in 2007. Has 11 years of teaching experience and has been an Associate Professor in the School of Information Technology and Engineering in Vellore Institute of Technology, Vellore. Her research area includes Image processing, soft computing, and data mining. She has around 20 papers in the reputed journal in her research field. She used to guide undergraduate and postgraduate students. Currently guiding doctoral students. She is a life member of CSI and IEEE. She is also part of various school activity committees.
R. Vettriselvan received his Bachelor (B.A.) of Economics from Madurai Kamaraj University; Master of Business Administration (MBA) from Anna University and Master of Philosophy (M.Phil.) Research and Development and received Doctorate from Gandhigram Rural Institute-Deemed University. He received ICSSR Doctoral Fellowship, ICSSR, New Delhi and GRI fellowship. He also received Post Graduate Diploma in Personnel Management and Industrial Relations from Alagappa University, Karaikudi. He is specialized in Human Resource Management and Marketing. He published 5 books and 65 research articles in SCOPUS/ UGC/ Referred International/ National Peer Reviewed Journals and Conference volumes. He presented more than 60 research articles in the National and International Conferences conducted in India, Zambia, Malawi and USA. He received travel grant award 2015 from Population Association of America, USA to present the research article in California, USA. Received best paper, best paper presenter, Best Young Faculty, Bright Educator and Best Academician of the year (Male) Most Promising Educators in Higher education Across in India in the year. He is an editorial and review board member for number of high impact factor peer reviewed journals. He is guiding three Ph.D. research scholars and guided 30 MBA and 86 undergraduate projects. He is specialized in Human Resource Management, Marketing and Finance. He has experience in NBA, NAAC Acceptation documentation process. He has 6 years experience in various capacities such as Manager, human Resources, NEST Abroad Studies Academy Private Limited, Madurai; Lecturer & Head of the Department, School of Commerce and Management, DMI-St. Eugene University, Zambia; Assistant Professor, AMET Business School, AMET University, India and Lecturer, School of Commerce and Management and Coordinator, Department of Research and Publication, DMI-St.John the Baptist University. He has acted as a Review Member for the National Council for Higher Education, Malawi from February2020 to June 2020 to review the Accreditation process. Currently working as Assistant Professor AMET Business School, AMET (Deemed to be University) Chennai.
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Paperback. Condition: new. Paperback. Data science revolves around two giants: Big Data analytics and Deep Learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of Big Data as well as Deep Learning systems.This book discusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and decision-making. It also covers numerous applications in healthcare, education, communication, media, and entertainment. Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics offers innovative platforms for integrating Big Data and Deep Learning and presents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval.FEATURESProvides insight into the skill set that leverages ones strength to act as a good data analystDiscusses how Big Data and Deep Learning hold the potential to significantly increase data understanding and help in decision-makingCovers numerous potential applications in healthcare, education, communication, media, and entertainmentOffers innovative platforms for integrating Big Data and Deep LearningPresents issues related to adequate data storage, semantic indexing, data tagging, and fast information retrieval from Big DataThis book is aimed at industry professionals, academics, research scholars, system modelers, and simulation experts. Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781032104461
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