Book Image

R Data Science Essentials

Book Image

R Data Science Essentials

Overview of this book

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.
Table of Contents (15 chapters)
R Data Science Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


In this chapter, you learned to create an attractive visualization using the googleVis package, create an interactive dashboard using the shiny package, and got a good understanding about the components of the app.

Finally, in this book, you learned some of the most essential data science concepts, such as basic data formatting to make the data ready for analysis, exploratory data analysis, pattern discovery using the Apriori algorithm, segmentation using the clustering algorithm, regression model, forecasting on the time series dataset, building a recommendation engine using the collaborative filtering method, and the creation of a dashboard to communicate with the user. Overall, you learned all of this with working examples and also real-life use cases where these can be applied.