FOUNDATION OF DATA SCIENCE

Dr. Santosh Kumar Sahu · Dr. Herison Surbakti · Ismail Keshta · Dr. Haewon Byeon

авг 2023. · Xoffencerpublication

E-knjiga

240

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O ovoj e-knjizi

The 1960s saw the beginning of computer science as an academic field of study. The programming languages, compilers, and operating systems, as well as the mathematical theory that underpinned these fields, were the primary focuses of this course. Finite automata, regular expressions, context-free languages, and computability were some of the topics that were addressed in theoretical computer science courses. In the 1970s, the study of algorithms became an essential component of theory when it had previously been neglected. The goal was to find practical applications for computers. At this time, a significant shift is taking place, and more attention is being paid to the diverse range of applications. This shift came about for a variety of different causes. The convergence of computer and communication technologies has been a significant contributor to this change. Our current conception of data and how best to work with it in a contemporary environment has to be revised in light of recent advances in the capacity to monitor, collect, and store data in a variety of domains, including the natural sciences, business, and other areas. The rise of the internet and social networks as fundamental components of everyday life carries with it a wealth of theoretical possibilities as well as difficulties. Traditional subfields of computer science continue to hold a significant amount of weight in the field as a whole, but researchers of the future will focus more on how to use computers to comprehend and extract usable information from massive amounts of data arising from applications rather than how to make computers useful for solving particular problems in a well-defined manner. With this in mind, we have prepared this book to cover the theory that we anticipate will be important in the next 40 years, in the same way that a grasp of automata theory, algorithms, and other similar areas provided students an advantage in the previous 40 years. An increased focus on probability, statistical approaches, and numerical methods is one of the key shifts that has taken place. The book's early draughts have been assigned reading at a variety of academic levels, from undergraduate to graduate. The appendix contains the necessary background information for a course taken at the 1 | P a ge undergraduate level. Because of this, the appendix contains problems for your homework.

O autoru

Dr. Santosh Kumar Sahu working as an Assistant Professor in the Department of Mechanical Engineering at Veer Surendra Sai University of Technology, Burla. He graduated in Mechanical Engineering at Synergy Institute of Engineering & Technology, Dhenkanal, Odisha, India. He secured Master of Technology in Mechanical Engineering (Production Engineering Specialization)at National Institute of Technology, Rourkela, Odisha, India. He secured Ph.D. in Mechanical Engineering at Jadavpur University, Kolkata, West Bengal, India. He is in the field of Mechanical Engineering at Veer Surendra Sai University of Technology, Burla, Sambalpur, Odisha, India. He is in teaching profession for more than 12 years. He has published55 number of papers in National and International Journals, Conference. He has also published five books and six patents. His main area of interest includes Non Traditional Machining, Modeling and Optimization of Production Processes Machining, Data Sciences, Decision and Information Sciences and Supply Chain Management.

Dr. Herison Surbakti has dedicated over a decade to teaching and supervising international undergraduate and postgraduate students, particularly in South East Asia, notably in Indonesia, Malaysia, and Thailand. Within the realm of Data Science, Dr. Surbakti's research interests gravitate towards Data Analytics, Business Intelligence, and Knowledge Management. He ardently explores groundbreaking approaches within these domains, striving to bridge the divide between academia and industry. His expertise and unwavering passion for these fields not only render him an invaluable asset to the academic community but also position him as an influential figure in advancing knowledge.

Ismail Keshta received his B.Sc. and the M.Sc. degrees in computer engineering and his Ph.D. in computer science and engineering from the King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, in 2009, 2011, and 2016, respectively. He was a lecturer in the Computer Engineering Department of KFUPM from 2012 to 2016. Prior to that, in 2011, he was a lecturer in Princess Nourahbint Abdulrahman University and Imam Muhammad ibn Saud Islamic University, Riyadh, Saudi Arabia. He is currently an assistant professor in the computer science and information systems department of AlMaarefa University, Riyadh, Saudi Arabia. His research interests include software process improvement, modeling, and intelligent systems.

Dr. Haewon Byeon received the DrSc degree in Biomedical Science from Ajou University School of Medicine. Haewon Byeon currently works at the Department of Medical Big Data, Inje University. His recent interests focus on health promotion, AI-medicine, and biostatistics. He is currently a member of international committee for a Frontiers in Psychiatry, and an editorial board for World Journal of Psychiatry. Also, He were worked on a 4 projects (Principal Investigator) from the Ministry of Education, the Korea Research Foundation, and the Ministry of Health and Welfare. Byeon has published more than 343 articles and 19 books.

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