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

This book is written both for readers entering the field, and for practitioners with a background in AI and an interest in developing real-world applications. T

Artificial Intelligence in Highway Safety provides cutting-edge advances in highway safety using AI. The author is a highway safety expert. He pursues highway s

Leverage top XAI frameworks to explain your machine learning models with ease and discover best practices and guidelines to build scalable explainable ML system

A Cookbook that will help you implement Machine Learning algorithms and techniques by building real-world projects Ê KEY FEATURESÊ Learn how to handle an enti

The objective of this textbook is to introduce students and professionals to fundamental principles and techniques and emerging technologies in energy informati