This is a companion discussion topic for the original entry at https://www.rstudio.com/blog/model-monitoring-with-r-markdown
ModelOps or MLOps (for “model/machine learning operations”) focuses on the real-world processes involved in building, deploying, and maintaining a model within an organization’s data infrastructure. Developing a model that meets your organizations needs and goals is a big accomplishment, but whether that model’s purpose is largely predictive, inferential, or descriptive, the “care and feeding” of your model often doesn’t end when you are done developing it. How is the model going to be deployed?