Description
Beginning Data Science in R 4 (2nd Ed., 2nd ed.)
Data Analysis, Visualization, and Modelling for the Data Scientist
Author: Mailund Thomas
Language: EnglishSubject for Beginning Data Science in R 4:
Keywords
R; programming; statistics; data science; big data; machine learning; deep learning; ai; cloud; analytics; coding; software
Publication date: 06-2022
511 p. · 17.8x25.4 cm · Paperback
511 p. · 17.8x25.4 cm · Paperback
Description
/li>Contents
/li>Biography
/li>Comment
/li>
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.
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 sets found in big data
- Build an R package
- Test and check your code
- Practice version control
- Profile and optimize your code
Who This Book Is For
Those with some data science or analytics background, but not necessarily experience with the R programming language.
1. Introduction to R programming.
2. Reproducible analysis.
3. Data manipulation.
4. Visualizing and exploring data.
5. Working with large data sets.
6. Supervised learning.
7. Unsupervised learning.
8. More R programming.
9. Advanced R programming.
10. Object oriented programming.
11. Building an R package.
12. Testing and checking.
13. Version control.
14. Profiling and optimizing.
Thomas Mailund is an associate professor in bioinformatics at Aarhus University, Denmark. His background is in math and computer science but for the last decade his main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species.
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 lecture series
© 2024 LAVOISIER S.A.S.