Free Shipping to all UK customers for orders over £25.00

0 Total items on my wish-list.

Free Shipping to all UK customers for orders over £25.00

Ryefieldbooks Logo

Ryefield Books

Free Shipping to all UK customers for orders over £25.00

Ryefieldbooks Logo

Ryefield Books

© Copyright Ryefield Books - All Right Reserved
Product Categories
My Shopping Cart
Void image

You shopping cart is empty

You may browse our offerings to locate what you're
searching for, then put it in your shopping cart.

Book cover image

Beginning Data Science in R 4

Usually dispatched within 3 - 5 business days.

In Stock (597)

£ 47.99

Description

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Beginning Data Science in R 4, Second Edition details how data science is a combination of statistics, computational science, and machine learning. You’ll see how to efficiently structure and mine data to extract useful patterns and build mathematical models. This requires computational methods and programming, and R is an ideal programming language for this. Modern data analysis requires computational skills and usually a minimum of programming. After reading and using this book, you'll have what you need to get started with R programming with data science applications. Source code will be available to support your next projects as well. Source code is available at github.com/Apress/beg-data-science-r4. What You Will LearnPerform data science and analytics using statistics and the R programming languageVisualize and explore data, including working with large data sets found in big dataBuild an R packageTest and check your codePractice version controlProfile and optimize your codeWho This Book Is ForThose with some data science or analytics background, but not necessarily experience with the R programming language.