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Practical Big Data Analytics

You're reading from   Practical Big Data Analytics Hands-on techniques to implement enterprise analytics and machine learning using Hadoop, Spark, NoSQL and R

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781783554393
Length 412 pages
Edition 1st Edition
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Author (1):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
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Table of Contents (13) Chapters Close

Preface 1. Too Big or Not Too Big FREE CHAPTER 2. Big Data Mining for the Masses 3. The Analytics Toolkit 4. Big Data With Hadoop 5. Big Data Mining with NoSQL 6. Spark for Big Data Analytics 7. An Introduction to Machine Learning Concepts 8. Machine Learning Deep Dive 9. Enterprise Data Science 10. Closing Thoughts on Big Data 11. External Data Science Resources 12. Other Books You May Enjoy

The Analytics Toolkit

There are several platforms today that are used for large-scale data analytics. At a broad level, these are divided into platforms that are used primarily for data mining, such as analysis of large datasets using NoSQL platforms, and those that are used for data science—that is, machine learning and predictive analytics. Oftentimes, the solution may have both the characteristics—a robust underlying platform for storing and managing data, and solutions that have been built on top of them that provide additional capabilities in data science.

In this chapter, we will show you how to install and configure your Analytics Toolkit, a collection of software that we'll use for the rest of the chapters:

  • Components of the Analytics Toolkit
  •  System recommendations
    • Installing on a laptop or workstation
    • Installing on the cloud
  • Installing Hadoop...
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