Mathematical Foundations of Data Science Using R

✍ Scribed by Frank Emmert-Streib; Salissou Moutari; Matthias Dehmer

• Publisher: De Gruyter Oldenbourg
• Year: 2020
• Tongue: English
• Leaves: 430
• Category: Library

✦ Synopsis

In order best exploit the incredible quantities of data being generated in most diverse disciplines data sciences increasingly gain worldwide importance. The book gives the mathematical foundations to handle data properly. It introduces basics and functionalities of the R programming language which has become the indispensable tool for data sciences. Thus it delivers the reader the skills needed to build own tool kits of a modern data scientist.

• Brilliant didactics
• Background information (also for non-specialists)
• Examples that illustrate the concepts and methods developed
• 4c pictures, completely 4c

✦ Table of Contents

Preface
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