Whrn you train your own models, you can use explainers to determine feature importance.
Before you start this lab, ensure that you have completed Lab 1A and Lab 1B, which include tasks to create the Azure Machine Learning workspace and other resources used in this lab.
In this task, you'll use explainers to interpret models.
- In Azure Machine Learning studio, view the Compute page for your workspace; and on the Compute Instances tab, ensure your compute instance is running. If not, start it.
- When the compute instance is running, click the Jupyter link to open the Jupyter home page in a new browser tab.
- In the Jupyter home page, in the Users/DP100 folder, open the 09B - Interpreting Models.ipynb notebook. Then read the notes in the notebook, running each code cell in turn.
Note: If you intend to continue straight to the next exercise, leave your compute instance running. If you're taking a break, you might want to close all Jupyter tabs and Stop your compute instance to avoid incurring unnecessary costs.