Network Data Analytics

A Hands-On Approach for Application Development

AvK. G. Srinivasa,Siddesh G. M.

Häftad, Engelska, 2018

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2018-12-26
Mått:155 x 235 x 22 mm
Vikt:728 g
Format:Häftad
Språk:Engelska
Serie:Computer Communications and Networks
Antal sidor:398
Förlag:Springer Nature Switzerland AG
ISBN:9783030085445

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Människa – datorinteraktion inom Data och IT
Databaser inom Data och IT

Mer om författaren

Dr. Krishnarajanagar GopalaIyengar Srinivasa is an associate professor and the head of the Department of IT at C.B.P. Government Engineering College, Jaffarpur, New Delhi, India. His other publications include the Springer book Guide to High Performance Distributed Computing. Dr. Gaddadevara Matt Siddesh is an associate professor at the Department of Information Science and Engineering at Ramaiah Institute of Technology, Bangalore, India. Srinidhi Hiriyannaiah is an assistant professor at the Department of Computer Science and Engineering at Ramaiah Institute of Technology, Bangalore, India.

Innehållsförteckning

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.