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 |
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| VerfasserIn: | |
| Place / Publishing House: | München ;, Wien : : De Gruyter Oldenbourg, , [2022] ©2022 |
| Year of Publication: | 2022 |
| Language: | English |
| Series: | De Gruyter STEM
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| Online Access: | |
| Physical Description: | 1 online resource (XVI, 408 p.) |
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Table of Contents:
- 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