Tidymodels Overview

The tidymodels ecosystem provides a consistent, modular framework for machine learning in R. Understanding the ecosystem context helps when working with any tidymodels pipeline before diving into package-specific details.

Core Principle: Recipes Are Plans, Not Actions

Critical: A recipe object is a specification of preprocessing steps. Adding steps like step_normalize() does not transform data immediately. Transformations execute only when:

1. prep() estimates parameters from training data
2. bake() applies the prepped recipe to new data

# This does NOT transform data - it creates a plan
rec <- recipe(outcome ~ ., data = train) |>
  step_normalize(all_numeric_predictors())

# This estimates parameters (means, sds) from training data
prepped <- prep(rec, training = train)