Emmert-Streib, Frank,
Mathematical Foundations of Data Science Using R / Frank Emmert-Streib, Salissou Moutari, Matthias Dehmer. - 1 online resource (XVI, 408 p.) - De Gruyter STEM .
Frontmatter -- Preface to the second edition -- Contents -- 1 Introduction -- Part I: Introduction to R -- 2 Overview of programming paradigms -- 3 Setting up and installing the R program -- 4 Installation of R packages -- 5 Introduction to programming in R -- 6 Creating R packages -- Part II: Graphics in R -- 7 Basic plotting functions -- 8 Advanced plotting functions: ggplot2 -- 9 Visualization of networks -- Part III: Mathematical basics of data science -- 10 Mathematics as a language for science -- 11 Computability and complexity -- 12 Linear algebra -- 13 Analysis -- 14 Differential equations -- 15 Dynamical systems -- 16 Graph theory and network analysis -- 17 Probability theory -- 18 Optimization -- Bibliography -- Index
restricted access http://purl.org/coar/access_right/c_16ec
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.
Mode of access: Internet via World Wide Web.
In English.
9783110796063
10.1515/9783110796063 doi
Computer science--Mathematics.
Computational Statistics.
Data Analytics.
Data Science.
R for Genomics.
COMPUTERS / Database Management / Data Mining.
Computational Statistics. Data Analysis. Data Analytics. Data Science.
QA76.9.M35 / E46 2022
004.0151
Mathematical Foundations of Data Science Using R / Frank Emmert-Streib, Salissou Moutari, Matthias Dehmer. - 1 online resource (XVI, 408 p.) - De Gruyter STEM .
Frontmatter -- Preface to the second edition -- Contents -- 1 Introduction -- Part I: Introduction to R -- 2 Overview of programming paradigms -- 3 Setting up and installing the R program -- 4 Installation of R packages -- 5 Introduction to programming in R -- 6 Creating R packages -- Part II: Graphics in R -- 7 Basic plotting functions -- 8 Advanced plotting functions: ggplot2 -- 9 Visualization of networks -- Part III: Mathematical basics of data science -- 10 Mathematics as a language for science -- 11 Computability and complexity -- 12 Linear algebra -- 13 Analysis -- 14 Differential equations -- 15 Dynamical systems -- 16 Graph theory and network analysis -- 17 Probability theory -- 18 Optimization -- Bibliography -- Index
restricted access http://purl.org/coar/access_right/c_16ec
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.
Mode of access: Internet via World Wide Web.
In English.
9783110796063
10.1515/9783110796063 doi
Computer science--Mathematics.
Computational Statistics.
Data Analytics.
Data Science.
R for Genomics.
COMPUTERS / Database Management / Data Mining.
Computational Statistics. Data Analysis. Data Analytics. Data Science.
QA76.9.M35 / E46 2022
004.0151