This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches

Resolve the black box models in your AI applications to make them fair, trustworthy, and secure. Familiarize yourself with the basic principles and tools to dep

Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black

A deep and detailed dive into the key aspects and challenges of machine learning interpretability, complete with the know-how on how to overcome and leverage th

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simp