Explainable AI: Foundations and Practical Techniques  (Paperback, Paresh Patil, Sushant Gaikwad, Akash Hatkangane)

Embark on an exciting journey into the frontier of Explainable AI (XAI) with this detailed and comprehensive guide, designed specifically to bridge the gap between the complex world of artificial intelligence and non-technical users who seek to navigate this landscape. Within this extensive resource, readers can delve into a variety of explanation methods and their critical evaluation, allowing for a thorough understanding of how these concepts play out in real-world scenarios. Furthermore, you will learn to adeptly apply data-centric XAI principles to develop practical solutions that address real challenges faced by businesses and researchers alike. Gain invaluable hands-on experience with an array of cutting-edge tools such as LIME, SHAP, TCAV, DALEX, ALIBI, and DiCE, enhancing your skill set and empowering your projects. Additionally, discover industrial best practices that can guide your efforts, while navigating open challenges with the help of recommended guidelines that foster clarity and efficiency. This essential resource not only promotes AI transparency and trustworthiness but also makes the adoption of AI technologies significantly easier for various applications in both industry and research domains. It is the perfect guide for anyone keen on understanding and effectively implementing explainable machine learning systems in their work.