Open source software for statistical analysis of big data: emerging research and opportunities
"This book explores topics in the field of open source software for big data"--
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2020.
|
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 |
| Zusammenfassung: | "This book explores topics in the field of open source software for big data"-- |
| Beschreibung: | 17 PDFs (237 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781799827702 |
| Zugangseinschränkungen: | Restricted to subscribers or individual electronic text purchasers. |
Internformat
MARC
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| 040 | |a CaBNVSL |b eng |e rda |c CaBNVSL |d CaBNVSL | ||
| 050 | 4 | |a QA276.4 |b .O64 2020e | |
| 082 | 7 | |a 005.7 |2 23 | |
| 245 | 0 | 0 | |a Open source software for statistical analysis of big data |b emerging research and opportunities |c Richard S. Segall and Gao Niu, editors. |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c 2020. | |
| 300 | |a 17 PDFs (237 Seiten) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a 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. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "This book explores topics in the field of open source software for big data"-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | 0 | |a Description based on title screen (IGI Global, viewed 02/15/2020). | |
| 650 | 0 | |a Big data. | |
| 650 | 0 | |a Open source software. | |
| 650 | 0 | |a Statistics |x Data processing. | |
| 650 | 7 | |a Big data. |2 fast | |
| 650 | 7 | |a Open source software. |2 fast | |
| 650 | 7 | |a Statistics |x Data processing. |2 fast | |
| 653 | |a Cluster Analysis. | ||
| 653 | |a Data Analytics. | ||
| 653 | |a Data Visualization. | ||
| 653 | |a Fatality Rate Modeling. | ||
| 653 | |a High Performance Computing. | ||
| 653 | |a Machine Learning. | ||
| 653 | |a Neural Networks. | ||
| 653 | |a Python. | ||
| 653 | |a R Programming. | ||
| 653 | |a Statistical Coding. | ||
| 653 | |a Time Series Forecasting. | ||
| 700 | 1 | |a Niu, Gao |d 1987- |e editor. | |
| 700 | 1 | |a Segall, Richard |d 1949- |e editor. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | |c (Original) |w (DLC)2019043972 | |
| 776 | 0 | 8 | |i Print version: |z 1799827682 |z 9781799827689 |w (DLC) 2019043972 |
| 966 | 4 | 0 | |l DE-862 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2768-9 |3 Volltext |
| 966 | 4 | 0 | |l DE-863 |p ZDB-98-IGB |q FWS_PDA_IGB |u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-2768-9 |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-862 | ||
| 049 | |a DE-863 | ||
Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-98-IGB-00237841 |
|---|---|
| _version_ | 1826942597893980160 |
| adam_text | |
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| author2 | Niu, Gao 1987- Segall, Richard 1949- |
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| author_facet | Niu, Gao 1987- Segall, Richard 1949- |
| building | Verbundindex |
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| callnumber-first | Q - Science |
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| callnumber-raw | QA276.4 .O64 2020e |
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| callnumber-subject | QA - Mathematics |
| collection | ZDB-98-IGB |
| contents | 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. |
| ctrlnum | (CaBNVSL)slc00000304 (OCoLC)1123182190 |
| dewey-full | 005.7 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security |
| dewey-raw | 005.7 |
| dewey-search | 005.7 |
| dewey-sort | 15.7 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| id | ZDB-98-IGB-00237841 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:33Z |
| institution | BVB |
| isbn | 9781799827702 |
| language | English |
| oclc_num | 1123182190 |
| open_access_boolean | |
| owner | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 17 PDFs (237 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | IGI Global |
| record_format | marc |
| spelling | Open source software for statistical analysis of big data emerging research and opportunities Richard S. Segall and Gao Niu, editors. Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2020. 17 PDFs (237 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier 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. Restricted to subscribers or individual electronic text purchasers. "This book explores topics in the field of open source software for big data"-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 02/15/2020). Big data. Open source software. Statistics Data processing. Big data. fast Open source software. fast Statistics Data processing. fast Cluster Analysis. Data Analytics. Data Visualization. Fatality Rate Modeling. High Performance Computing. Machine Learning. Neural Networks. Python. R Programming. Statistical Coding. Time Series Forecasting. Niu, Gao 1987- editor. Segall, Richard 1949- editor. IGI Global, publisher. (Original) (DLC)2019043972 Print version: 1799827682 9781799827689 (DLC) 2019043972 |
| spellingShingle | Open source software for statistical analysis of big data emerging research and opportunities 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. Big data. Open source software. Statistics Data processing. Big data. fast Open source software. fast Statistics Data processing. fast |
| title | Open source software for statistical analysis of big data emerging research and opportunities |
| title_auth | Open source software for statistical analysis of big data emerging research and opportunities |
| title_exact_search | Open source software for statistical analysis of big data emerging research and opportunities |
| title_full | Open source software for statistical analysis of big data emerging research and opportunities Richard S. Segall and Gao Niu, editors. |
| title_fullStr | Open source software for statistical analysis of big data emerging research and opportunities Richard S. Segall and Gao Niu, editors. |
| title_full_unstemmed | Open source software for statistical analysis of big data emerging research and opportunities Richard S. Segall and Gao Niu, editors. |
| title_short | Open source software for statistical analysis of big data |
| title_sort | open source software for statistical analysis of big data emerging research and opportunities |
| title_sub | emerging research and opportunities |
| topic | Big data. Open source software. Statistics Data processing. Big data. fast Open source software. fast Statistics Data processing. fast |
| topic_facet | Big data. Open source software. Statistics Data processing. |
| work_keys_str_mv | AT niugao opensourcesoftwareforstatisticalanalysisofbigdataemergingresearchandopportunities AT segallrichard opensourcesoftwareforstatisticalanalysisofbigdataemergingresearchandopportunities AT igiglobal opensourcesoftwareforstatisticalanalysisofbigdataemergingresearchandopportunities |