Book description
A handson guide for professionals to perform various data science tasks in R
Key Features
 Explore the popular R packages for data science
 Use R for efficient data mining, text analytics and feature engineering
 Become a thorough data science professional with the help of handson examples and usecases in R
Book Description
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 handson with realworld 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 largescale data analytics without much complexity.
What you will learn
 Understand the R programming language and its ecosystem of packages for data science
 Obtain and clean your data before processing
 Master essential exploratory techniques for summarizing data
 Examine various machine learning prediction, models
 Explore the H2O analytics platform in R for deep learning
 Apply data mining techniques to available datasets
 Work with interactive visualization packages in R
 Integrate R with Spark and Hadoop for largescale data analytics
Who this book is for
If you are a budding data scientist keen to learn about the popular pandas library, or a Python developer looking to step into the world of data analysis, this book is the ideal resource you need to get started. Some programming experience in Python will be helpful to get the most out of this course
Publisher resources
Table of contents
 Title Page
 Copyright and Credits
 About Packt
 Contributors
 Preface
 Getting Started with Data Science and R
 Descriptive and Inferential Statistics

Data Wrangling with R
 Introduction to data wrangling with R

Data extraction, transformation, and load
 Basic tools of data wrangling
 Using base R for data manipulation and analysis
 Applying families of functions 
 Using data.table for data manipulation
 Reading and writing files with data.table
 A special note on dates and/or time
 Miscellaneous topics
 Tutorial – looking at airline flight times data
 Summary
 Quiz
 KDD, Data Mining, and Text Mining
 Data Analysis with R
 Machine Learning with R
 Forecasting and ML App with R
 Neural Networks and Deep Learning
 Markovian in R
 Visualizing Data
 Going to Production with R
 Large Scale Data Analytics with Hadoop
 R on Cloud
 The Road Ahead
 Other Books You May Enjoy
Product information
 Title: HandsOn Data Science with R
 Author(s):
 Release date: November 2018
 Publisher(s): Packt Publishing
 ISBN: 9781789139402
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