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Titlebook: Beginning Data Science in R 4; Data Analysis, Visua Thomas Mailund Book 2022Latest edition Thomas Mailund 2022 R.programming.statistics.dat

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发表于 2025-3-21 18:32:26 | 显示全部楼层 |阅读模式
期刊全称Beginning Data Science in R 4
期刊简称Data Analysis, Visua
影响因子2023Thomas Mailund
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发行地址Gives you everything you need to know to get started in data science using R language.Updated for R programming language version 4.0.A unique book by a data science expert and is based on a successful
图书封面Titlebook: Beginning Data Science in R 4; Data Analysis, Visua Thomas Mailund Book 2022Latest edition Thomas Mailund 2022 R.programming.statistics.dat
影响因子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
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Mandayam A. Srinivasan,Robert H. LaMotte later, when we have a little more experience using R. The good news is, though, that to use R for data analysis, we rarely need to do much programming. At least, if you do the right kind of programming, you won’t need much.
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Introduction to R Programming, later, when we have a little more experience using R. The good news is, though, that to use R for data analysis, we rarely need to do much programming. At least, if you do the right kind of programming, you won’t need much.
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