Registering existing models
In this exercise, you will take two existing MLflow Models and register them to the MLflow Model Registry to begin managing the lifecycle of both models. Each of these models was trained using the "Insurance"
data at a previous date to predict if an insurance claim was for a male or female.
The first model can be found in the local directory "model_2022"
and was never logged to MLflow Tracking. The second model was logged to MLflow Tracking under the artifact URI of "model_2023"
. Its run_id
attribute has been saved as a variable named "run_id"
.
The mlflow
module will be imported.
This exercise is part of the course
Introduction to MLflow
Exercise instructions
- Register the first model in directory
model_2022
as a model named"Insurance"
. - Register the second model to
"Insurance"
using an f-string literal forrun_id
and the artifact URI.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Register the first (2022) model
____.____("____", "____")
# Register the second (2023) model
____.____(f"____", "____")