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