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 endUnderstand how to use different modeling and feature engineering approaches fluentlyExamine the options for avoiding common pitfalls of modeling, such as overfittingLearn practical methods to prepare your data for modelingTune models for optimal performanceUse good statistical practices to compare, evaluate, and choose among models
