Model evaluation is arguably the most important step of the modeling process. As data scientists we constantly make decisions based on these evaluations. Is model A better than model B? Will this model be profitable in production? Is performance in production declining? Model evaluation for humans discusses approaches for assessing our models practically in ways we understand.

Practitioners who are relatively new to releasing models into production or a product are likely to benefit the most from this talk however data scientists of all abilities may find useful strategies to take away. The approaches that we will discuss serve better as a play book than a rule book and will help build confidence in your model throughout all phases of the business lifecycle from development through deployment.