Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
The Statistics and Machine Learning with R Workshop

You're reading from   The Statistics and Machine Learning with R Workshop Unlock the power of efficient data science modeling with this hands-on guide

Arrow left icon
Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781803240305
Length 516 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Liu Peng Liu Peng
Author Profile Icon Liu Peng
Liu Peng
Arrow right icon
View More author details
Toc

Table of Contents (20) Chapters Close

Preface 1. Part 1:Statistics Essentials
2. Chapter 1: Getting Started with R FREE CHAPTER 3. Chapter 2: Data Processing with dplyr 4. Chapter 3: Intermediate Data Processing 5. Chapter 4: Data Visualization with ggplot2 6. Chapter 5: Exploratory Data Analysis 7. Chapter 6: Effective Reporting with R Markdown 8. Part 2:Fundamentals of Linear Algebra and Calculus in R
9. Chapter 7: Linear Algebra in R 10. Chapter 8: Intermediate Linear Algebra in R 11. Chapter 9: Calculus in R 12. Part 3:Fundamentals of Mathematical Statistics in R
13. Chapter 10: Probability Basics 14. Chapter 11: Statistical Estimation 15. Chapter 12: Linear Regression in R 16. Chapter 13: Logistic Regression in R 17. Chapter 14: Bayesian Statistics 18. Index 19. Other Books You May Enjoy

Fundamentals of R Markdown

R Markdown is a formatting language that can help you effectively and dynamically reveal insights from the data and generate reports in the form of a PDF, an HTML file, or a web application. It allows you to tidy up your analyses via various forms of graphs and tables covered earlier in this book, and present them in a consistent, neat, and transparent manner that facilitates easy reproduction by another analyst. Either in academia or industry, demonstrating reproducibility in your analysis is an essential quality of your work. When others can easily reproduce and understand what you did in your analysis, it makes communication much easier and your work more trustworthy. Since all outputs are code-based, the ability to easily reproduce your work also makes it convenient to fine-tune the analysis when you present your initial work and come back with further modifications to be done, a common iterative process in real-life data analysis.

Using R Markdown...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at AU $24.99/month. Cancel anytime