As machine learning becomes increasingly integral to decisions that affect health, safety, economic wellbeing, and other aspects of people's lives, it's important to be able to understand how models make predictions; and to be able to explain the rationale for machine learning based decisions.

In this session you will learn how to:

* Interpret global and local feature importance.
* Use an explainer to interpret a model.
* Create model explanations in a training experiment.
* Visualize model explanations.