R Data Science Essentials

Learn the essence of data science and visualization using R in no time at all

About This Book

• Become a pro at making stunning visualizations and dashboards quickly and without hassle
• For better decision making in business, apply the R programming language with the help of useful statistical techniques
• From seasoned authors comes a book that offers you a plethora of fast-paced techniques to detect and analyze data patterns

Who This Book Is For

If you are an aspiring data scientist or analyst who has a basic understanding of data science and has basic hands-on experience in R or any other analytics tool, then R Data Science Essentials is the book for you.

What You Will Learn

• Perform data preprocessing and basic operations on data
• Implement visual and non-visual implementation data exploration techniques
• Mine patterns from data using affinity and sequential analysis
• Use different clustering algorithms and visualize them
• Implement logistic and linear regression and find out how to evaluate and improve the performance of an algorithm
• Extract patterns through visualization and build a forecasting algorithm
• Build a recommendation engine using different collaborative filtering algorithms
• Make a stunning visualization and dashboard using ggplot and R shiny

In Detail

With organizations increasingly embedding data science across their enterprise and with management becoming more data-driven it is an urgent requirement for analysts and managers to understand the key concept of data science. The data science concepts discussed in this book will help you make key decisions and solve the complex problems you will inevitably face in this new world.

R Data Science Essentials will introduce you to various important concepts in the field of data science using R. We start by reading data from multiple sources, then move on to processing the data, extracting hidden patterns, building predictive and forecasting models, building a recommendation engine, and communicating to the user through stunning visualizations and dashboards.

By the end of this book, you will have an understanding of some very important techniques in data science, be able to implement them using R, understand and interpret the outcomes, and know how they helps businesses make a decision.

Key Features

• Become a pro at making stunning visualizations and dashboards quickly and without hassle
• For better decision making in business, apply the R programming language with the help of useful statistical techniques.
• From seasoned authors comes a book that offers you a plethora of fast-paced techniques to detect and analyze data patterns

Book Description

With organizations increasingly embedding data science across their enterprise and with management becoming more data-driven it is an urgent requirement for analysts and managers to understand the key concept of data science. The data science concepts discussed in this book will help you make key decisions and solve the complex problems you will inevitably face in this new world.

R Data Science Essentials will introduce you to various important concepts in the field of data science using R. We start by reading data from multiple sources, then move on to processing the data, extracting hidden patterns, building predictive and forecasting models, building a recommendation engine, and communicating to the user through stunning visualizations and dashboards.

By the end of this book, you will have an understanding of some very important techniques in data science, be able to implement them using R, understand and interpret the outcomes, and know how they helps businesses make a decision.

What you will learn

• Perform data preprocessing and basic operations on data
• Implement visual and non-visual implementation data exploration techniques
• Mine patterns from data using affinity and sequential analysis
• Use different clustering algorithms and visualize them
• Implement logistic and linear regression and find out how to evaluate and improve the performance of an algorithm
• Extract patterns through visualization and build a forecasting algorithm
• Build a recommendation engine using different collaborative filtering algorithms
• Make a stunning visualization and dashboard using ggplot and R shiny

About the Author

Raja B. Koushik is a business intelligence professional with over 7 years of experience and is currently working in one of the leading international IT services companies. His primary interest lies for business intelligence technologies, such as ETL, reporting, and dashboarding, along with analytics based on statistics. He has worked with one of the world's largest companies for both their U.S. as well as UK business in the healthcare and leasing domains. He holds an engineering degree with specialization in information technology from Anna University.

Sharan Kumar Ravindran is a data scientist with over 5 years of experience and is currently working with a leading e-commerce company in India. His primary interest lies in statistics and machine learning, and he has worked with multiple customers across Europe and the U.S. in the e-commerce and IoT domains. He holds an MBA degree with specialization in marketing and business analysis. He conducts workshops, partnering with Anna University, to train their staff, research scholars, and volunteers in analytics. In addition to co-authoring Data Science Essentials with R by Packt Publishing, Sharan has also co-authored Mastering Social Media Mining with R by Packt Publishing. He maintains www.rsharankumar.com, a website with links to his social profiles and data blog.

Table of Contents

1. Getting Started with R
2. Exploratory Data Analysis
3. Pattern Discovery
4. Segmentation Using Clustering
5. Developing Regression Models
6. Time Series Forecasting
7. Recommendation Engine
8. Communicating Data Analysis