Kuhn Max, Silge Julia. Tidy Modeling with R: A Framework for Modeling in the Tidyverse

O’Reilly Media, Inc., 2022. — 381 p. — ISBN13: 978-1-492-09648-1.Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting 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 to 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.Software for Modeling.
A Tidyverse Primer.
A Review of R Modeling Fundamentals.
Modeling Basics
The Ames Housing Data.
Spending Our Data.
Fitting Models with parsnip.
A Model Workflow.
Feature Engineering with Recipes.
Judging Model Effectiveness.
Tools for Creating Effective Models
Resampling for Evaluating Performance.
Comparing Models with Resampling.
Model Tuning and the Dangers of Overfitting.
Grid Search.
Iterative Search.
Screening Many Models.
Beyond the Basics
Dimensionality Reduction.
Encoding Categorical Data.
Explaining Models and Predictions.
When Should You Trust Your Predictions?
Ensembles of Models.
Inferential Analysis.