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WELCOME10 for flat 10% instant discount on checkout.Explore the frontier of Explainable AI (XAI) with this comprehensive guide, bridging the gap between artificial intelligence and non-technical users. Delve into various explanation methods and their evaluation, and learn to apply data-centric XAI for practical solutions. Gain hands-on experience with tools like LIME, SHAP, TCAV, DALEX, ALIBI, and DiCE. Discover industrial best practices and address open challenges using recommended guidelines. This essential resource promotes AI transparency and trustworthiness, making AI adoption easier for both industry and research applications. Perfect for anyone looking to understand and implement explainable machine learning systems.
Complete unabridged work with full editorial oversight
80 GSM acid-free paper built to resist yellowing
Section-sewn spine crafted for lay-flat reading
Distinguished Literary Contributor
Akash Hatkangane is a renowned author whose cataloged publications are preserved in our repository.
“A seminal addition to any library. Lucid, insightful, and meticulously researched from first principles.”
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