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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

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781803240305
Length 516 pages
Edition 1st Edition
Languages
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Author (1):
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Liu Peng Liu Peng
Author Profile Icon Liu Peng
Liu Peng
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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

Summary

In this chapter, we introduced R Markdown, a flexible, transparent, and consistent report-generation tool. We started by going over the fundamentals of R Markdown, including the basic building blocks such as YAML headers and code chunks, followed by text formatting techniques.

Next, we covered a case study using Google’s stock data. After downloading the stock data from the web, we generated a report to summarize the statistics of the daily closing price, added plots and tables to the report, performed data processing, and displayed the results with different styling options. We also explored a few different ways to configure a code chunk.

Lastly, we discussed how to customize the R Markdown reports. The topics we covered included adding a table of contents to the report, creating repetitive reports using parameters in the YAML header, and changing the visual style of the report by editing the visual properties of different components using CSS.

With the next...

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