Mathematical Foundations of Data Science Using R /

Mathematical Foundations of Data Science Using R / / Frank Emmert-Streib, Salissou Moutari, Matthias Dehmer.

The aim of the book is to help students become data scientists. Since this requires a series of courses over a considerable period of time, the book intends to accompany students from the beginning to an advanced understanding of the knowledge and skills that define a modern data scientist. The book...

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Superior document:Title is part of eBook package: De Gruyter DG Plus DeG Package 2022 Part 1
VerfasserIn:
Emmert-Streib, Frank,
Dehmer, Matthias,
Moutari, Salissou,
Place / Publishing House:München ;, Wien : : De Gruyter Oldenbourg, , [2022]
©2022
Year of Publication:2022
Language:English
Series:De Gruyter STEM
Online Access:
Physical Description:1 online resource (XVI, 408 p.)
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245 1 0 |a Mathematical Foundations of Data Science Using R /  |c Frank Emmert-Streib, Salissou Moutari, Matthias Dehmer. 
264 1 |a München ;  |a Wien :   |b De Gruyter Oldenbourg,   |c [2022] 
264 4 |c ©2022 
300 |a 1 online resource (XVI, 408 p.) 
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505 0 0 |t Frontmatter --   |t Preface to the second edition --   |t Contents --   |t 1 Introduction --   |t Part I: Introduction to R --   |t 2 Overview of programming paradigms --   |t 3 Setting up and installing the R program --   |t 4 Installation of R packages --   |t 5 Introduction to programming in R --   |t 6 Creating R packages --   |t Part II: Graphics in R --   |t 7 Basic plotting functions --   |t 8 Advanced plotting functions: ggplot2 --   |t 9 Visualization of networks --   |t Part III: Mathematical basics of data science --   |t 10 Mathematics as a language for science --   |t 11 Computability and complexity --   |t 12 Linear algebra --   |t 13 Analysis --   |t 14 Differential equations --   |t 15 Dynamical systems --   |t 16 Graph theory and network analysis --   |t 17 Probability theory --   |t 18 Optimization --   |t Bibliography --   |t Index 
506 0 |a restricted access  |u http://purl.org/coar/access_right/c_16ec  |f online access with authorization  |2 star 
520 |a The aim of the book is to help students become data scientists. Since this requires a series of courses over a considerable period of time, the book intends to accompany students from the beginning to an advanced understanding of the knowledge and skills that define a modern data scientist. The book presents a comprehensive overview of the mathematical foundations of the programming language R and of its applications to data science. 
530 |a Issued also in print. 
538 |a Mode of access: Internet via World Wide Web. 
546 |a In English. 
588 0 |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 29. Mai 2023) 
650 0 |a Computer science  |x Mathematics. 
650 4 |a Computational Statistics. 
650 4 |a Data Analytics. 
650 4 |a Data Science. 
650 4 |a R for Genomics. 
650 7 |a COMPUTERS / Database Management / Data Mining.  |2 bisacsh 
653 |a Computational Statistics. 
653 |a Data Analysis. 
653 |a Data Analytics. 
653 |a Data Science. 
700 1 |a Dehmer, Matthias,   |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Moutari, Salissou,   |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
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