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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

Product type Paperback

Published in Oct 2023

Publisher Packt

ISBN-13 9781803240305

Length 516 pages

Edition 1st Edition

Languages

R

Concepts

Data Science

Author (1):

Liu Peng

View More author details

Table of Contents (20) Chapters

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

Why subscribe?

19. Other Books You May Enjoy

Technical requirements

To run the code in this chapter, you will need to have the latest versions of the following packages:

ggplot2, 3.4.0
dplyr, 1.0.10

Please note that the versions of the packages mentioned in the preceding list are the latest ones at the time of writing this chapter.

The code and data for this chapter is available at https://github.com/PacktPublishing/The-Statistics-and-Machine-Learning-with-R-Workshop/blob/main/Chapter_10/working.R.

The rest of the chapter is locked

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Authors (1)

Liu Peng

Liu Peng

Peng Liu is an Assistant Professor of Quantitative Finance (Practice) at Singapore Management University and an adjunct researcher at the National University of Singapore. He holds a Ph.D. in statistics from the National University of Singapore and has ten years of working experience as a data scientist across the banking, technology, and hospitality industries.

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