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  • Book Overview & Buying Hands-On Data Science with R
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Hands-On Data Science with R

Hands-On Data Science with R

By : Doug Ortiz , Vitor Bianchi Lanzetta, Nataraj Dasgupta, Ricardo Anjoleto Farias
4 (1)
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Hands-On Data Science with R

Hands-On Data Science with R

4 (1)
By: Doug Ortiz , Vitor Bianchi Lanzetta, Nataraj Dasgupta, Ricardo Anjoleto Farias

Overview of this book

R is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world. This book covers the entire data science ecosystem for aspiring data scientists, right from zero to a level where you are confident enough to get hands-on with real-world data science problems. The book starts with an introduction to data science and introduces readers to popular R libraries for executing data science routine tasks. This book covers all the important processes in data science such as data gathering, cleaning data, and then uncovering patterns from it. You will explore algorithms such as machine learning algorithms, predictive analytical models, and finally deep learning algorithms. You will learn to run the most powerful visualization packages available in R so as to ensure that you can easily derive insights from your data. Towards the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity.
Table of Contents (16 chapters)
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The UI and server

Each R Shiny application consists of two primary sections, which are the UI section and the server section. The UI, as the name suggests, is used to define the user interface, whereas the server section is used for executing the underlying R server side code. The shinyApp function is used in order to launch the application using the ui and server definitions.

The UI object holds the R Shiny widgets used to prepare the frontend components that the user will interact with while using the application.

A few toy examples have already been included as part of the RStudio programming environment. In order to launch an R Shiny application, run the following code in RStudio:

library(shiny)
runExample("01_hello")

This will launch a basic R Shiny app, shown as follows:

You can view the other applications available as examples by simply executing the following...

CONTINUE READING
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