Exercise

MLflow experiments

MLflow experiments are used as a way to organize data from training runs in a way that can be easily searched and queried for our analysis later.

In this exercise, you will use the MLflow module to create a new experiment called Unicorn Model for your new ML project. You will add useful information to the experiment by setting tags for the version. Finally, you will set the Unicorn Model experiment as your current experiment so when you begin tracking your data will be tracked within this particular experiment.

Instructions

100 XP

Import the MLflow module.
Create a new experiment called "Unicorn Model".
On the Unicorn Model, set the set the tags as "version" and "1.0".
Set the experiment "Unicorn Model" as the current experiment for tracking.