Cantitate/Preț
Produs
Total produse
Vezi coșul
Network Data Analytics: A Hands-On Approach for Application Development de K. G. Srinivasa

Network Data Analytics: A Hands-On Approach for Application Development: Computer Communications and Networks

Autor K. G. Srinivasa, Siddesh G. M., Srinidhi H.
en Limba Engleză Hardback – 14 mai 2018
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.

Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 66900 lei  38-44 zile
  Springer International Publishing – 26 dec 2018 66900 lei  38-44 zile
Hardback (1) 68009 lei  38-44 zile
  Springer International Publishing – 14 mai 2018 68009 lei  38-44 zile

Din seria Computer Communications and Networks

Preț: 68009 lei

Preț vechi: 85011 lei
-20% Nou

Puncte Express: 1020
Preț estimativ în valută:
13017€ • 13567$ • 10836£

Carte tipărită la comandă

Livrare economică 02-08 ianuarie 25

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783319777993
ISBN-10: 3319777998
Pagini: 398
Ilustrații: XXV, 398 p. 155 illus., 117 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.85 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seria Computer Communications and Networks

Locul publicării:Cham, Switzerland

Cuprins

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.

Notă biografică

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.

Textul de pe ultima copertă

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 inrelated fields, and is also of interest to general readers with an understanding of data analytics.

Caracteristici

Introduces tools for data analytics, machine learning for data analytics, and for exploring and visualizing data Suitable as both a practical guide and a reference for researchers and students Provides supplementary material, in the form of working source code, on an associated website Includes supplementary material: sn.pub/extras