Beginning Data Science in R 4: Data Analysis, Visualization, and Modelling for the Data Scientist
Author: Thomas Mailund
Publisher: Apress; 2nd edition (June 24, 2022)
Language: English
Paperback: 539 pages
ISBN-10: 1484281543
ISBN-13: 9781484281543
Book Description
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.
Modern data analysis requires computational skills and usually a minimum of programming. After reading and using this book, you’ll have what you need to get started with R programming with data science applications. Source code will be available to support your next projects as well.
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
Beginning Data Science in R 4: Data Analysis, Visualization, and Modelling for the Data Scientist, 2nd Edition
未经允许不得转载:finelybook » Beginning Data Science in R 4: Data Analysis, Visualization, and Modelling for the Data Scientist, 2nd Edition
相关推荐
- High Performance Control of AC Drives With Matlab / Simulink Models
- x64 Assembly Language Step-by-Step: Programming with Linux, 4th Edition
- Math Learning Strategies: How Parents and Teachers Can Help Kids Excel in Math
- Model-Based Reinforcement Learning: From Data to Continuous Actions with a Python-based Toolbox
finelybook
