Principles of Data Science by Hamid R Arabnia

Principles of Data Science by Hamid R Arabnia

This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists’ preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science.

• Introduces various techniques, methods, and algorithms adopted by Data Science experts
• Provides a detailed explanation of data science perceptions, reinforced by practical examples
• Presents a road map of future trends suitable for innovative data science research and practice

Professor Hamid R. Arabnia received a Ph.D. degree in Computer Science from the University of Kent (England) in 1987. He is currently a Professor Emeritus of Computer Science at University of Georgia, USA, where he has been since October 1987. His research interests include parallel and distributed processing techniques & algorithms, supercomputing, Data Science, imaging science, and other compute intensive problems. Applications of interest include: medical imaging and security. Most recent activities include: Studying ways to promote legislation that would prevent cyber-stalking, cyber-harassment, and cyber-bullying. As a victim of cyber-harassment and cyber-bullying, in 2017 he won a lawsuit with damages awarded to him for a total of $2.3 Million and $656K attorney costs. Since this court case was one of the few cases of its kind in the United States, this ruling is considered to be important; Final Judgement for damages was issued in Leon County Courthouse of Tallahassee in Florida by Circuit Court Judge. Prof. Arabnia is Editor-in-Chief of The Journal of Supercomputing (Springer). He is also on the editorial and advisory boards of 30 other journals. He is the book series editor-in-chief of Transactions of Computational Science and Computational Intelligence (Springer). He has won 12 distinguished awards, including the Outstanding Research Contributions to the Field of Supercomputing (President of IEEE/SMC) and Distinguished Research Award for Outstanding Contributions to Adaptable Communication Systems (ACM SIGAPP IMCOM). Dr. Arabnia is Fellow and Advisor of Center of Excellence in Terrorism, Resilience, Intelligence & Organized Crime Research (CENTRIC). He has been a PI/Co-PI on about $8 Million externally funded projects, about $200K internally funded projects, and about $4 Million equipment grants. During his tenure as Director of Graduate Programs, Dr. Arabnia secured the largest level of funding in the history of the department for supporting the research and education of graduate students (PhD, MS). Dr. Arabnia has delivered a number of keynote and plenary lectures at international conferences; most recently at: The 14th IEEE International Conference on Parallel and Distributed Systems (ICPADS, Australia); International Conference on Future Generation Communication and Networking (FGCN / IEEE CS, Sanya); The 10th IEEE International Conference on High Performance Computing and Communications (HPCC, Dalian); and ACM IMCOM International Conference. He has also delivered a number of distinguished lectures at various universities and research units/centers (USA, Spain, South Korea, Japan, Iran, Saudi Arabia, UK, Canada, Turkey, China, Ireland, Australia, ...); his distinguished lectures were funded and sponsored by US Department of Defense, SERSC of Republic of Korea, US National Science Foundation, H2020 of Europe, and others.

Dr. Leonidas Deligiannidis is a Professor of Computer Science at Wentworth Institute of Technology in Boston, MA. His foundation in Computer Science was first established when he earned his B.S. from Northeastern University College of Computer Science. He then went on to obtain two advanced degrees in the field from Tufts University. He has been active in the field since then, investigating subjects like Brain Computer Interfaces, Security, Business-oriented visualizations, and STEM Education. He has also served in industrial positions outside the scope of his academic work, using his acumen for several companies. His industry experience includes both entrepreneur startups in healthcare and high-tech networking companies. He has received multiple awards for his efforts, including multiple Achievement Awards for his contributions to Imaging Science by the World Congress in Computer Science, Computer Engineering, and Applied Computing, IEEE best paper awards, as well as a University Presidential award for his scholarly achievements. In addition, he has served as a referee for many journals in computer science and is a member of the program and organizing committees for notable conferences in his field.

Professor Hayaru Shouno received his Ph.D degree from Osaka University, Japan in 1999. He is a professor of the University of Electro-Communications (Japan) from 2015. His research interests include artificial intelligence, artificial neural networks, and vision. He is the chair of Technical committee of neurocomputing (NC) in the Institute of Electronics, Information and Communication Engineers (IEICE) in Japan.

Fernando G. Tinetti has a PhD in Computer Science and is a Professor at Facultad de Informatica, Universidad Nacional de La Plata, La Plata, Argentina. He is also a researcher of the Comision Investigaciones Cientificas de la Provincia de Buenos Aires, Argentina. He is a recipient of the NSF-TCPP Early Adopter Award, NSF/IEEE-TCPP, Curriculum Initiative on Parallel and Distributed Computing. He is the author/co-author of more than one hundred papers in International Journals and Computer Science Conferences. His areas of interest and experience include: High Performance Computing, Parallel and Distributed Computing, Cloud and Edge Computing, Real-Time Systems and Applications, Big Data Processing, Data Center and Infrastructure Performance Evaluation, Robotic Systems and Applications. He has co-edited a number of books in HPC.

Prof. Dr. Quoc-Nam Tran is a full professor of Computer Science at Southeastern Louisiana University (SELU). Before moving to SELU, he was the Chair of Computer Science at the University of South Dakota, the flagship university of South Dakota. His research areas include computational methods and algorithmic foundations especially the computational methods for big data analysis and high performance computing in bioinformatics. Dr. Tran is the author/editor of 70 publications including three research books published by Springer and Elsevier. He served as the General Chair and PC members of the many international conferences. He also served as an editor for books in the Elsevier Computer Science Reviews and Trends Series. Prof. Tran has industrial experiment in the area of software tools for computational methods. He has won many awards and has chaired a number of workshops and sessions for major conferences.

SKU	Unavailable
ISBN 13	9783030439804
ISBN 10	3030439801
Title	Principles of Data Science
Author	Hamid R Arabnia
Series	Transactions On Computational Science And Computational Intelligence
Condition	Unavailable
Binding Type	Hardback
Publisher	Springer Nature Switzerland AG
Year published	2020-07-09
Number of pages	276
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.