Explainable AI: Foundations, Methodologies and Applications by Mayuri Mehta Pape
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Explainable AI: Foundations, Methodologies and Applications by Mayuri Mehta
In the rapidly evolving field of artificial intelligence, the concept of explainability has become increasingly important. With the rise of complex machine learning models such as deep neural networks, there is a growing need for AI systems to be able to provide explanations for their decisions and predictions.
In her groundbreaking book, “Explainable AI: Foundations, Methodologies and Applications,” author Mayuri Mehta delves into the fundamental principles and techniques behind explainable AI. Mehta explores the various methodologies and approaches that can be used to make AI systems more transparent and interpretable, allowing users to understand how and why a particular decision was made.
From the theoretical foundations of explainability to real-world applications in areas such as healthcare, finance, and autonomous driving, Mehta covers a wide range of topics in this comprehensive guide. Readers will gain a deeper understanding of the challenges and opportunities associated with making AI systems more explainable, and learn how to implement these techniques in their own projects.
Whether you are a seasoned AI practitioner looking to enhance the transparency of your models, or a newcomer to the field seeking to understand the inner workings of AI systems, “Explainable AI” is a must-read resource. Join Mayuri Mehta on a journey through the complex world of explainable AI, and discover how this emerging field is shaping the future of artificial intelligence.
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