Step by step with tidymodels

A real world application

Machine learning for optimizing waiting time

Part 1: Data and problem

Based on real word data, from a hospital I introduce tidymodeling. I tried to reduce the waiting time for an operation using tidymodeling.
Here are the data and some explanations of the entire project.

Part 2: Basic operations

This part introduces data splitting, the basic recipe, the first model, workflow and the first fit.

Part 3: Resampling

Shows resampling, tuning with grid search and parallel processing here.

Part 4: Final modeling

This part adds information from texts to the model using the library:tidytext and demonstrates the final modeling.

Part 5: Deploying the model

Here I show how to deploy the model using vetiver.

The presentation of the project got the AHFE 2023 Best Paper Award.