The Art of Explaining Predictions

An important part of a data scientist's role is to explain model predictions. Often, the person receiving the explanation will be non-technical. If you start talking about cost functions, hyperparameters or p-values you will be met with blank stares. We need to translate these technical concepts into layman's terms. This process can be more challenging than building the model itself. We will explore how you can give human-friendly explanations. We will do this by discussing some key characteristics of a good explanation. The focus will be on explaining individual predictions.