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  3. Introduction to MLflow

Exercise

Starting a run

MLflow uses the concept of a run as a way to organize model training. Before metrics, parameters or artifacts can be logged to MLflow Tracking, a run must become active. Each run must also belong to an existing experiment.

In the following exercise, you will start a new run so that you can begin logging a model. You will also set the experiment in which you would like the run to be logged. The mlflow module will already be imported for you.

Instructions

100 XP
  • Set the experiment so that the active run tracks to "Unicorn Sklearn Experiment" experiment.
  • Start a new run with mlflow module.