R for Data Analysis in easy steps contains separate chapters on the major features of the R programming language. There are complete example programs that demonstrate how to create Line graphs, Bar charts, Histograms, Scatter graphs, Box plots, and more. The code for each R script is listed, together with screenshots that illustrate the actual output when that script has been executed. The free, downloadable example R code is provided for clearer...

This handy reference book detailing the intricacies of R updates the popular first edition by adding R version 3.4 and 3.5 features. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. Some of the new material includes information on RStudio, S4 syntax, working with character strings,...

"This book provides an overall introduction to R with a focus on tools and methods commonly used in Data Science, with an emphasis on practice and business use. The intention is to provide a practical guide for non-experts with a focus on business users. The author covers a wide range of topics in a single book: databases, statistical machine learning, data wrangling, data visualization, and reporting such results. The book includes seven parts. Part...

Want to use the power of R sooner rather than later? Don't have time to plow through wordy texts and online manuals? Use this book for quick, simple code to get your projects up and running. It includes code and examples applicable to many disciplines. Written in everyday language with a minimum of complexity, each chapter provides the building blocks you need to fit R's astounding capabilities to your analytics, reporting, and visualization needs....

With the open source R programming language and its immense library of packages, you can perform virtually any data analysis task. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to import, manipulate, summarize, model, and plot data with R; formalize analytical code; and build powerful R packages using current best practices. Each short, easy lesson builds on all that's come before: you'll learn...

This book is ideal for people wanting to get up-and-running with the core concepts of machine learning using R 3.5. This book follows a step-by-step approach to implementing an end-to-end pipeline, addressing data collection and processing, various types of data analysis, and machine learning use cases.

Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and more Key Features Master machine learning, deep learning, and predictive modeling concepts in R 3.5 Build intelligent end-to-end projects for finance, retail, social media, and a variety of domains Implement smart cognitive models with helpful tips and best practices Book Description R is one of the most popular languages when it comes to performing...

A hands-on, readable guide to machine learning with R. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights and make new predictions. The 3rd edition features newer and better libraries, advice on ethical and bias issues, and an introduction to deep learning.

R Programming for Actuarial Science Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work. In R Programming for Actuarial Science, readers will find: Basic theory for each chapter to complement other...

"Teaches a range of machine learning methods, from simple to complex. Includes dozens of illustrative examples using the R programming language and real datasets. Covers not only how to use machine learning methods but also why these methods work and advice on how to avoid common pitfalls"--