Who this book is for
This book caters to a diverse audience, including:
- Data professionals who face the growing challenge of explaining the functioning of AI systems they create and manage and seek ways to enhance them.
- Data scientists and machine learning professionals aiming to broaden their expertise by learning model interpretation techniques and strategies to overcome model challenges from fairness to robustness.
- Aspiring data scientists who have a basic grasp of machine learning and proficiency in Python.
- AI ethics officers aiming to deepen their knowledge of the practical aspects of their role to guide their initiatives more effectively.
- AI project supervisors and business leaders eager to integrate interpretable machine learning in their operations, aligning with the values of fairness, responsibility, and transparency.
