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Beginning Data Science in R 4

Name: Beginning Data Science in R 4
Author: Thomas Mailund

Data Analysis, Visualization, and Modelling for the Data Scientist

Thomas Mailund

PDF

ca. 56,99 €

Amazon 27,99 € iTunes Thalia.de Hugendubel Bücher.de ebook.de kobo Osiander Google Books Barnes&Noble bol.com Legimi yourbook.shop Kulturkaufhaus ebooks-center.de
* Affiliatelinks/Werbelinks

Apress

Naturwissenschaften, Medizin, Informatik, Technik / Programmiersprachen

Beschreibung

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