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  3. Machine learning

Beginning Data Science in R 4

- Data Analysis, Visualization, and Modelling for the Data Scientist
Af: Thomas Mailund Engelsk Paperback

Beginning Data Science in R 4

- Data Analysis, Visualization, and Modelling for the Data Scientist
Af: Thomas Mailund Engelsk Paperback
Tjek vores konkurrenters priser
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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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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Produktdetaljer
Sprog: Engelsk
Sider: 511
ISBN-13: 9781484281543
Indbinding: Paperback
Udgave:
ISBN-10: 1484281543
Kategori: Machine learning
Udg. Dato: 24 jun 2022
Længde: 32mm
Bredde: 253mm
Højde: 176mm
Forlag: APress
Oplagsdato: 24 jun 2022
Forfatter(e): Thomas Mailund
Forfatter(e) Thomas Mailund

Kategori Machine learning

ISBN-13 9781484281543

Sprog Engelsk

Indbinding Paperback

Sider 511

Udgave

Længde 32mm

Bredde 253mm

Højde 176mm

Udg. Dato 24 jun 2022

Oplagsdato 24 jun 2022

Forlag APress

Kategori sammenhænge