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Open source software for statistical...
~
Niu, Gao, (1987-)
Open source software for statistical analysis of big dataemerging research and opportunities /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Open source software for statistical analysis of big dataRichard S. Segall and Gao Niu, editors.
Reminder of title:
emerging research and opportunities /
other author:
Segall, Richard,
Published:
Hershey, Pennsylvania :IGI Global,2020.
Description:
1 online resource (xiv, 237 p.)
Subject:
StatisticsData processing.
Online resource:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2768-9
ISBN:
9781799827702 (ebk.)
Open source software for statistical analysis of big dataemerging research and opportunities /
Open source software for statistical analysis of big data
emerging research and opportunities /[electronic resource] :Richard S. Segall and Gao Niu, editors. - Hershey, Pennsylvania :IGI Global,2020. - 1 online resource (xiv, 237 p.)
Includes bibliographical references and index.
Chapter 1. What is open source software (OSS) and what is big data? -- Chapter 2. Open source software (OSS) for big data -- Chapter 3. Introduction to the popular open source statistical software (OSSS) -- Chapter 4. Cluster analysis in R with big data applications -- Chapter 5. Generalized linear model for automobile fatality rate prediction in R -- Chapter 6. Introduction to python and its statistical applications -- Chapter 7. A comparison of machine learning algorithms of big data for time series forecasting using python.
"This book explores topics in the field of open source software for big data"--
ISBN: 9781799827702 (ebk.)Subjects--Topical Terms:
183693
Statistics
--Data processing.
LC Class. No.: QA276.4 / .O64 2020
Dewey Class. No.: 005.7
Open source software for statistical analysis of big dataemerging research and opportunities /
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emerging research and opportunities /
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Richard S. Segall and Gao Niu, editors.
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Includes bibliographical references and index.
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Chapter 1. What is open source software (OSS) and what is big data? -- Chapter 2. Open source software (OSS) for big data -- Chapter 3. Introduction to the popular open source statistical software (OSSS) -- Chapter 4. Cluster analysis in R with big data applications -- Chapter 5. Generalized linear model for automobile fatality rate prediction in R -- Chapter 6. Introduction to python and its statistical applications -- Chapter 7. A comparison of machine learning algorithms of big data for time series forecasting using python.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2768-9
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EB QA276.4 .O64 2020 2020
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2768-9
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