Tidy Modeling with R: A Framework for Modeling in the Tidyverse


Tidy Modeling with R: A Framework for Modeling in the Tidyverse
Author:: Max Kuhn (Author), Julia Silge (Author)
Publisher finelybook 出版社: O’Reilly Media
Edition 版次: 1st
Publication Date 出版日期: 2022-08-16
Language 语言: English
Print Length 页数: 381 pages
ISBN-10: 1492096482
ISBN-13: 9781492096481


Book Description
By finelybook

Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you’re just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work.

RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You’ll understand why the tidymodels framework has been built to be used by a broad range of people.

With this book, you will:

  • Learn the steps necessary to build a model from beginning to end
  • Understand how to use different modeling and feature engineering approaches fluently
  • Examine the options for avoiding common pitfalls of modeling, such as overfitting
  • Learn practical methods to prepare your data for modeling
  • Tune models for optimal performance
  • Use good statistical practices to compare, evaluate, and choose among models


Review

The tidymodels framework combines human-centric design with statistical best practices, and I can’t think of a better way to learn it than from Max and Julia.
— 
Hadley Wickham (Chief Scientist, RStudio)
This book offers a unified and systematic approach to building, analyzing and evaluating statistical models in R.
Balasubramanian Narasimhan (Senior Research Scientist, Stanford University)

About the Author

Max Kuhn is a software engineer at RStudio. He is currently working on improving R’s modeling capabilities. He was applying models in the pharmaceutical and diagnostic industries for over 18 years. Max has a Ph.D. in Biostatistics and is the author of numerous R packages for techniques in machine learning. He, and Kjell Johnson, wrote the book “Applied Predictive Modeling”, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015. Their second book, “Feature Engineering and Selection”, was published in 2019.
Julia Silge is a software engineer at RStudio PBC where she works on open source modeling tools. She holds a PhD in astrophysics and has worked as a data scientist in tech and the nonprofit sector, as well as a technical advisory committee member for the US Bureau of Labor Statistics. She is an author of multiple books, an international keynote speaker, and a real-world practitioner focusing on data analysis and machine learning practice. Julia loves text analysis, making beautiful charts, and communicating about technical topics with diverse audiences.

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