Beginning Data Science In R 4 Data Analysis Visualization And Modelling For The Data Scientist Second Edition 2nd Edition Thomas Mailund by Thomas Mailund 9781484281543, 1484281543 instant download after payment.

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 Learn
• Perform data science and analytics using statistics and the R programming language
• Visualize and explore data, including working with large data sets found in big data
• Build an R package
• Test and check your code
• Practice version control
• Profile and optimize your code
 
Who This Book Is For
Those with some data science or analytics background, but not necessarily experience with the R programming language.