Explainable AI for Practitioners

Most intermediate machine learning books concentrate on optimizing models, whether by raising accuracy or by lowering prediction error. That focus often leaves out something important: understanding why and how a model arrives at the predictions it makes.

Explainable AI for Practitioners is a hands-on guide to the explainability methods that fill this gap. It brings together leading techniques for understanding model behavior. Experienced machine learning engineers and data scientists will learn how each technique works, so they can use these tools more easily in their everyday workflow.