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Beginning Data Science in R 4 : Data Analysis, Visualization, and Modelling for the Data Scientist - 2nd ed.

By: (Author) Thomas Mailund

Extended Catalogue

Ksh 9,000.00

Format: Paperback / Softback

ISBN-10: 1484281543

ISBN-13: 9781484281543

Edition: 2nd ed.

Publisher: APress

Imprint: APress

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jun 24th, 2022

Print length: 511 Pages

Weight: 1,004 grams

Dimensions (height x width x thickness): 17.60 x 25.30 x 3.20 cms

Product Classification: Compilers
Databases
Machine learning

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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.

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