Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/968
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dc.contributor.authorSrinivasa, K. G. ;en_US
dc.contributor.authorG. M., Siddesh. ;en_US
dc.contributor.authorH., Srinidhi. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:59Z-
dc.date.available2020-05-17T08:23:59Z-
dc.date.issued2018en_US
dc.identifier.isbn9783319778006 ;en_US
dc.identifier.isbn9783319777993 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/968-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9783319777993. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractIn order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics. ;en_US
dc.description.statementofresponsibilityby K. G. Srinivasa, Siddesh G. M., Srinidhi H.en_US
dc.description.tableofcontentsPart I: Data Analytics and Hadoop -- Chapter 1. Introduction to Data Analytics -- Chapter 2. Introduction to Hadoop -- Chapter 3. Data Analytics with Map Reduce -- Part II: Tools for Data Analytics -- Chapter 4. Apache Pig -- Chapter 5. Apache Hive -- Chapter 6. Apache Spark -- Chapter 7. Apache Flume -- Chapter 8. Apache Storm -- Chapter 9. Python R -- Part III: Machine Learning for Data Analytics -- Chapter 10. Basics of Machine Learning -- Chapter 11. Linear Regression -- Chapter 12. Logistic Regression -- Chapter 13. Machine Learning on Spark -- Part IV: Exploring and Visualizing Data -- Chapter 14. Introduction to Visualization -- Chapter 15. Principles of Data Visualization -- Chapter 16. Visualization Charts -- Chapter 17. Popular Visualization Tools -- Chapter 18. Data Visualization with Hadoop -- Part V: Case Studies -- Chapter 19. Product Recommendation -- Chapter 20. Market Basket Analysis. ;en_US
dc.format.extentXXV, 398 p. 155 illus., 117 illus. in color. ; online resource. ;en_US
dc.publisherSpringer International Publishing :en_US
dc.publisherImprint: Springer,en_US
dc.relation.ispartofseriesComputer Communications and Networks, ; 1617-7975. ;en_US
dc.relation.ispartofseriesComputer Communications and Networks, ; 1617-7975. ;en_US
dc.relation.haspart9783319778006.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectData Miningen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectMathematics. ;en_US
dc.subjectVisualization. ;en_US
dc.subjectComputer Scienceen_US
dc.subjectData Mining and Knowledge Discoveryen_US
dc.subjectBig Data. ;en_US
dc.subjectVisualization. ;en_US
dc.subjectArtificial Intelligence and Roboticsen_US
dc.subject.ddc006.312 ; 23 ;en_US
dc.subject.lccQA76.9.D343 ;en_US
dc.titleNetwork Data Analyticsen_US
dc.title.alternativeA Hands-On Approach for Application Development /en_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
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9783319778006.pdf8.98 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSrinivasa, K. G. ;en_US
dc.contributor.authorG. M., Siddesh. ;en_US
dc.contributor.authorH., Srinidhi. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:59Z-
dc.date.available2020-05-17T08:23:59Z-
dc.date.issued2018en_US
dc.identifier.isbn9783319778006 ;en_US
dc.identifier.isbn9783319777993 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/968-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9783319777993. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractIn order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics. ;en_US
dc.description.statementofresponsibilityby K. G. Srinivasa, Siddesh G. M., Srinidhi H.en_US
dc.description.tableofcontentsPart I: Data Analytics and Hadoop -- Chapter 1. Introduction to Data Analytics -- Chapter 2. Introduction to Hadoop -- Chapter 3. Data Analytics with Map Reduce -- Part II: Tools for Data Analytics -- Chapter 4. Apache Pig -- Chapter 5. Apache Hive -- Chapter 6. Apache Spark -- Chapter 7. Apache Flume -- Chapter 8. Apache Storm -- Chapter 9. Python R -- Part III: Machine Learning for Data Analytics -- Chapter 10. Basics of Machine Learning -- Chapter 11. Linear Regression -- Chapter 12. Logistic Regression -- Chapter 13. Machine Learning on Spark -- Part IV: Exploring and Visualizing Data -- Chapter 14. Introduction to Visualization -- Chapter 15. Principles of Data Visualization -- Chapter 16. Visualization Charts -- Chapter 17. Popular Visualization Tools -- Chapter 18. Data Visualization with Hadoop -- Part V: Case Studies -- Chapter 19. Product Recommendation -- Chapter 20. Market Basket Analysis. ;en_US
dc.format.extentXXV, 398 p. 155 illus., 117 illus. in color. ; online resource. ;en_US
dc.publisherSpringer International Publishing :en_US
dc.publisherImprint: Springer,en_US
dc.relation.ispartofseriesComputer Communications and Networks, ; 1617-7975. ;en_US
dc.relation.ispartofseriesComputer Communications and Networks, ; 1617-7975. ;en_US
dc.relation.haspart9783319778006.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectData Miningen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectMathematics. ;en_US
dc.subjectVisualization. ;en_US
dc.subjectComputer Scienceen_US
dc.subjectData Mining and Knowledge Discoveryen_US
dc.subjectBig Data. ;en_US
dc.subjectVisualization. ;en_US
dc.subjectArtificial Intelligence and Roboticsen_US
dc.subject.ddc006.312 ; 23 ;en_US
dc.subject.lccQA76.9.D343 ;en_US
dc.titleNetwork Data Analyticsen_US
dc.title.alternativeA Hands-On Approach for Application Development /en_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319778006.pdf8.98 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSrinivasa, K. G. ;en_US
dc.contributor.authorG. M., Siddesh. ;en_US
dc.contributor.authorH., Srinidhi. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:59Z-
dc.date.available2020-05-17T08:23:59Z-
dc.date.issued2018en_US
dc.identifier.isbn9783319778006 ;en_US
dc.identifier.isbn9783319777993 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/968-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9783319777993. ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractIn order to carry out data analytics, we need powerful and flexible computing software. However the software available for data analytics is often proprietary and can be expensive. This book reviews Apache tools, which are open source and easy to use. After providing an overview of the background of data analytics, covering the different types of analysis and the basics of using Hadoop as a tool, it focuses on different Hadoop ecosystem tools, like Apache Flume, Apache Spark, Apache Storm, Apache Hive, R, and Python, which can be used for different types of analysis. It then examines the different machine learning techniques that are useful for data analytics, and how to visualize data with different graphs and charts. Presenting data analytics from a practice-oriented viewpoint, the book discusses useful tools and approaches for data analytics, supported by concrete code examples. The book is a valuable reference resource for graduate students and professionals in related fields, and is also of interest to general readers with an understanding of data analytics. ;en_US
dc.description.statementofresponsibilityby K. G. Srinivasa, Siddesh G. M., Srinidhi H.en_US
dc.description.tableofcontentsPart I: Data Analytics and Hadoop -- Chapter 1. Introduction to Data Analytics -- Chapter 2. Introduction to Hadoop -- Chapter 3. Data Analytics with Map Reduce -- Part II: Tools for Data Analytics -- Chapter 4. Apache Pig -- Chapter 5. Apache Hive -- Chapter 6. Apache Spark -- Chapter 7. Apache Flume -- Chapter 8. Apache Storm -- Chapter 9. Python R -- Part III: Machine Learning for Data Analytics -- Chapter 10. Basics of Machine Learning -- Chapter 11. Linear Regression -- Chapter 12. Logistic Regression -- Chapter 13. Machine Learning on Spark -- Part IV: Exploring and Visualizing Data -- Chapter 14. Introduction to Visualization -- Chapter 15. Principles of Data Visualization -- Chapter 16. Visualization Charts -- Chapter 17. Popular Visualization Tools -- Chapter 18. Data Visualization with Hadoop -- Part V: Case Studies -- Chapter 19. Product Recommendation -- Chapter 20. Market Basket Analysis. ;en_US
dc.format.extentXXV, 398 p. 155 illus., 117 illus. in color. ; online resource. ;en_US
dc.publisherSpringer International Publishing :en_US
dc.publisherImprint: Springer,en_US
dc.relation.ispartofseriesComputer Communications and Networks, ; 1617-7975. ;en_US
dc.relation.ispartofseriesComputer Communications and Networks, ; 1617-7975. ;en_US
dc.relation.haspart9783319778006.pdfen_US
dc.subjectComputer Scienceen_US
dc.subjectData Miningen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectMathematics. ;en_US
dc.subjectVisualization. ;en_US
dc.subjectComputer Scienceen_US
dc.subjectData Mining and Knowledge Discoveryen_US
dc.subjectBig Data. ;en_US
dc.subjectVisualization. ;en_US
dc.subjectArtificial Intelligence and Roboticsen_US
dc.subject.ddc006.312 ; 23 ;en_US
dc.subject.lccQA76.9.D343 ;en_US
dc.titleNetwork Data Analyticsen_US
dc.title.alternativeA Hands-On Approach for Application Development /en_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319778006.pdf8.98 MBAdobe PDFThumbnail
Preview File