Work with Model Predictions and Track Model Performance

Overview

Creating and visualizing model predictions takes advantage of many different types of R content and the ability to deploy them on RStudio Connect.

  • Predictions can be made available in a web application and to other services via an API

  • Continuous monitoring of the predictions can be used to watch for model drift and changes in goodness-of-fit over time

Demo content

The following model deployments in RStudio Connect are from the Bike Prediction example.

The bike prediction model outputs data in two ways:

Depending on the relative frequency of model retraining and input data refreshes, either of these can be a good way to serve model data.

The model performance app allows for comparisons over time between models:

Full Example: https://solutions.rstudio.com/tour/bike_predict/

Git Repository: https://github.com/sol-eng/bike_predict

Next steps

Learn: RStudio Connect 1.7.6 - Publish Git-backed Content

Try: Publishing Plumber APIs in RStudio Connect User Guide