Intro to Tidy Modeling
This is a resource intended to provide a top-level introduction into the main aspects of tidymodels. The introduction into tidyverse concepts largely adapted from Thomas Mock’s Intro to the Tidyverse. Content was also adapted from the Max Kuhn’s Applied Machine Learning content as well as Edgar Ruiz’s Gentle Introduction to Tidymodels.
View source code here.
Intro to Tidy modeling
This repository contains the resources used for a brief (~1hr) introduction to tidymodels.
The slides xaringan.Rmd briefly introduce the fundamentals of the tidymodels (parsnip, recipes, and rsample).
The API and app are based on the model created in audio_classifier.R. This creates a lyric classifier as outlined in mirr.
This model is then “productionalized” with plumber (plumber.R), and then wrapped in a small Shiny app (app.R).
Important notes
In order to run the prediction plumber API and Shiny App, a Spotify API key will be needed. The training data was collected with the spotifyr package. Refer to the spotifyr README for insstructions. I stored the credentials in an .Renviron file.