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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

To get the most out of this book

To get the most out of this book, it’s advisable to have a basic understanding of programming, ideally in R, although a strong foundation in any programming language should suffice. Familiarity with elementary statistics and mathematical concepts will also be beneficial, as the book delves into statistical methods and mathematical models. While the book is structured to guide you from foundational to advanced topics, prior exposure to data analysis techniques will enhance your learning experience. If you’re new to R, you may want to spend some extra time on the initial chapters to become comfortable with the programming environment and syntax.

Software covered in the book

Operating system requirements

R

Windows, macOS, or Linux

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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