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.