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Network data analyticsa hands-on app...

G. M., Siddesh.

Network data analyticsa hands-on approach for application development /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Network data analyticsby K. G. Srinivasa, Siddesh G. M., Srinidhi H.
其他題名:	a hands-on approach for application development /
作者:	Srinivasa, K. G.
其他作者:	G. M., Siddesh.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xxv, 398 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Electronic data processingDistributed processing.
電子資源:	http://dx.doi.org/10.1007/978-3-319-77800-6
ISBN:	9783319778006$q(electronic bk.)

Network data analyticsa hands-on approach for application development /
Srinivasa, K. G.

Network data analyticsa hands-on approach for application development /[electronic resource] :by K. G. Srinivasa, Siddesh G. M., Srinidhi H. - Cham :Springer International Publishing :2018. - xxv, 398 p. :ill. (some col.), digital ;24 cm. - Computer communications and networks,1617-7975. - Computer communications and networks..

Part 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.

In 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.

ISBN: 9783319778006$q(electronic bk.)

Standard No.: 10.1007/978-3-319-77800-6doiSubjects--Topical Terms:

182427
Electronic data processing
--Distributed processing.

LC Class. No.: QA76.9.D5

Dewey Class. No.: 004.6

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