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. The book is a great resource for practitioners and researchers in both industry and academia, and the discussed case studies and associated material can serve as inspiration for a variety of projects and hands-on assignments in a classroom setting. I will certainly keep this book as a personal resource for the courses I teach, and strongly recommend it to my students.
CITATION STYLE
Kamath, U., & Liu, J. (2021). Explainable artificial intelligence: An introduction to interpretable machine learning. Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning (pp. 1–310). Springer International Publishing. https://doi.org/10.1007/978-3-030-83356-5
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