Books by r

Books on R are educational and practical publications devoted to the study of the programming language R, which is widely used in statistics, data science, bioinformatics and machine learning. They provide both basic knowledge and advanced tools for working with large amounts of information.

What R Study on Books Involves

1. Syntax basics - variables, functions, data structures.
2. Statistical analysis - methods of data processing and interpretation.
3. Visualization - plotting and charting using packages (* ggplot2 *, * lattice *).
4. Working with big data - Using packages to process large tables and databases.
5. Machine learning - classification, regression and clustering algorithms.

Advantages of books by R

Systematic - a consistent presentation of the material.
Code examples - you can immediately apply knowledge in practice.
Level structure - there are books for both beginners and professionals.
Practical tasks - help to consolidate the material.

Examples of popular books

* "R for Data Science" by Hadley Wickham and Garrett Groulemund - an introduction to data analysis and visualization.
* Norman Matloff's "The Art of R Programming" is a book for those who want to learn more about language.
* Max Kuhn's Applied Predictive Modeling is a practical guide to machine learning in R.
* "Advanced R "by Hadley Wickham - for advanced level.

Current trends

Today, R books are actively published in electronic formats and are accompanied by online resources, code examples and interactive tasks. Many integrate with data analytics and learning platforms such as Coursera or DataCamp.

Find: Books by r