Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities
Language: English
Published by IGI Global, US, 2020
- Softcover
- New
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AbeBooks seller since June 11, 2025
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Seller Inventory # LU-9781799827696
- Title
- Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities
- Author
- Segall, Richard S.
- Publisher
- IGI Global, US
- Publication year
- 2020
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1799827690
- ISBN 13
- 9781799827696
Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.
"Synopsis" may belong to another edition of this title.
About the Author
Gao Niu is an Assistant Professor in Actuarial Science and Program Coordinator of Actuarial Math Program at Bryant University. He also serves as the Faculty Consultant of the Janet & Mark L Goldenson Center for Actuarial Research at the University of Connecticut. He has a doctorate in actuarial science from the University of Connecticut, is an Associate of the Casualty Actuarial Society and a Member of the American Academy of Actuaries. Dr. Niu has years of experience in academic actuarial research and consulting practice. His research area includes but not limited to the following: big data analytics application in insurance industry, property and casualty insurance practice, predictive modeling, agent-based modeling, financial planning, life insurance and health insurance pricing, reserving and data mining.
"About the title" may belong to another edition of this title.
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