R Data Analysis Projects

Get valuable insights from your data by building data analysis systems from scratch with R.About This BookA handy guide to take your understanding of data analysis with R to the next levelReal-world projects that focus on problems in finance, network analysis, social media, and moreFrom data manipulation to analysis to visualization in R, this book will teach you everything you need to know about building end-to-end data analysis pipelines using RWho This Book Is ForIf you are looking for a book that takes you all the way through the practical application of advanced and effective analytics methodologies in R, then this is the book for you. A fundamental understanding of R and the basic concepts of data analysis is all you need to get started with this book.What You Will LearnBuild end-to-end predictive analytics systems in RBuild an experimental design to gather your own data and conduct analysisBuild a recommender system from scratch using different approachesUse and leverage RShiny to build reactive programming applicationsBuild systems for varied domains including market research, network analysis, social media analysis, and moreExplore various R Packages such as RShiny, ggplot, recommenderlab, dplyr, and find out how to use them effectivelyCommunicate modeling results using Shiny DashboardsPerform multi-variate time-series analysis prediction, supplemented with sensitivity analysis and risk modelingIn DetailR offers a large variety of packages and libraries for fast and accurate data analysis and visualization. As a result, it's one of the most popularly used languages by data scientists and analysts, or anyone who wants to perform data analysis. This book will demonstrate how you can put to use your existing knowledge of data analysis in R to build highly efficient, end-to-end data analysis pipelines without any hassle.You'll start by building a content-based recommendation system, followed by building a project on sentiment analysis with tweets. You'll implement time-series modeling for anomaly detection, and understand cluster analysis of streaming data. You'll work through projects on performing efficient market data research, building recommendation systems, and analyzing networks accurately, all provided with easy to follow codes.With the help of these real-world projects, you'll get a better understanding of the challenges faced when building data analysis pipelines, and see how you can overcome them without compromising on the efficiency or accuracy of your systems. The book covers some popularly used R packages such as dplyr, ggplot2, RShiny, and others, and includes tips on using them effectively.By the end of this book, you'll have a better understanding of data analysis with R, and be able to put your knowledge to practical use without any hassle.Style and approachThis book takes a unique, learn-as-you-do approach, as you build on your understanding of data analysis progressively with each project. This book is designed in a way that implementing each project will empower you with a unique skill set, and enable you to implement the next project more confidently.