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The Statistics and Machine Learning with R Workshop

You're reading from The Statistics and Machine Learning with R Workshop

Product type Book

Published in Oct 2023

Publisher Packt

ISBN-13 9781803240305

Pages 516 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Liu Peng

Table of Contents (20) Chapters

Preface

1. Part 1:Statistics Essentials

2. Chapter 1: Getting Started with R

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

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

abline 115

accuracy rate 438

adjusted R2 394

aesthetics layer 101

analysis of variance (ANOVA) 336, 371, 384, 385

antiderivative 281, 296, 297

Area Under the Curve (AUC) 274, 438

arithmetic operations, R 9, 10

arrange() function 41

used, for sorting dataset 41-43

artificial intelligence (AI) 274

B

bar chart 119

building 124-127

Bayesian inference 465

normal-normal model 465

performing, with categorical variable 477-479

Bayesian linear regression

with categorical variable 477

Bayesian statistics 454

Bayesian theorem 454-456

Bernoulli-distributed random variables

analyzing 304-306

simulating 304-306

Bernoulli distribution 304

Bernoulli trial 302, 304

bigram representation 92

binary cross-entropy loss (CEL) 436

...

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Authors (1)

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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