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Big Data Analytics with R

You're reading from Big Data Analytics with R Leverage R Programming to uncover hidden patterns in your Big Data

Product type Paperback

Published in Jul 2016

Publisher Packt

ISBN-13 9781786466457

Length 506 pages

Edition 1st Edition

Languages

R

Tools

Hadoop

Concepts

Big Data

Author (1):

Simon Walkowiak

View More author details

Table of Contents (10) Chapters

Preface

1. The Era of Big Data FREE CHAPTER

2. Introduction to R Programming Language and Statistical Environment

3. Unleashing the Power of R from Within

4. Hadoop and MapReduce Framework for R

5. R with Relational Database Management Systems (RDBMSs)

6. R with Non-Relational (NoSQL) Databases

7. Faster than Hadoop - Spark with R

8. Machine Learning Methods for Big Data in R

9. The Future of R - Big, Fast, and Smart Data

Revisiting R basics

In the following section we will present a short revision of the most useful and frequently applied R functions and statements. We will start from a quick R and RStudio installation guide and then proceed to creating R data structures, data manipulation, and transformation techniques, and basic methods used in Exploratory Data Analysis (EDA). Although the R codes listed in this book have been tested extensively, as always in such cases, please make sure that your equipment is not faulty and note that you will be running all the following scripts at your own risk.

Getting R and RStudio ready

Depending on your operating system (whether Mac OS X, Windows, or Linux) you can download and install specific base R files directly from https://cran.r-project.org/ . If you prefer to use RStudio IDE you still need to install the R core available from CRAN website first and then download and run installers of the most recent version of RStudio IDE specific for your platform from...

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Authors (1)

Walkowiak

Walkowiak

Simon Walkowiak is a cognitive neuroscientist and a managing director of Mind Project Ltd a Big Data and Predictive Analytics consultancy based in London, United Kingdom. As a former data curator at the UK Data Service (UKDS, University of Essex) European largest socio-economic data repository, Simon has an extensive experience in processing and managing large-scale datasets such as censuses, sensor and smart meter data, telecommunication data and well-known governmental and social surveys such as the British Social Attitudes survey, Labour Force surveys, Understanding Society, National Travel survey, and many other socio-economic datasets collected and deposited by Eurostat, World Bank, Office for National Statistics, Department of Transport, NatCen and International Energy Agency, to mention just a few. Simon has delivered numerous data science and R training courses at public institutions and international companies. He has also taught a course in Big Data Methods in R at major UK universities and at the prestigious Big Data and Analytics Summer School organized by the Institute of Analytics and Data Science (IADS).

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