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Hands-On Data Science with R

You're reading from   Hands-On Data Science with R Techniques to perform data manipulation and mining to build smart analytical models using R

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789139402
Length 420 pages
Edition 1st Edition
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Authors (4):
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Nataraj Dasgupta Nataraj Dasgupta
Author Profile Icon Nataraj Dasgupta
Nataraj Dasgupta
Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Author Profile Icon Vitor Bianchi Lanzetta
Vitor Bianchi Lanzetta
Doug Ortiz Doug Ortiz
Author Profile Icon Doug Ortiz
Doug Ortiz
Ricardo Anjoleto Farias Ricardo Anjoleto Farias
Author Profile Icon Ricardo Anjoleto Farias
Ricardo Anjoleto Farias
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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Data Science and R FREE CHAPTER 2. Descriptive and Inferential Statistics 3. Data Wrangling with R 4. KDD, Data Mining, and Text Mining 5. Data Analysis with R 6. Machine Learning with R 7. Forecasting and ML App with R 8. Neural Networks and Deep Learning 9. Markovian in R 10. Visualizing Data 11. Going to Production with R 12. Large Scale Data Analytics with Hadoop 13. R on Cloud 14. The Road Ahead 15. Other Books You May Enjoy

Installing the package and Spark

To begin, you need to install a few packages and the Spark itself. To do it, call the following codes; it can take some time to download Spark:

install.packages(c("dplyr", "sparklyr", "DAAG"))
library(sparklyr); library(dplyr)

#installing Spark
spark_install()

The DAAG package contains the dataset we are going to use. So, let's start our learning. This chapter is divided into five sections plus this introduction. The next section teaches you how to manipulate Spark data using dplyr and SQL query. In the second section, we bring Spark data into R, for analysis and visualization. The third section shows how to use the Spark or the H2O machine learning algorithms. The fourth section presents the Spark API. Lastly, there is a final section to see the Spark connection on RStudio IDE.

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