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Explainable Artificial Intelligence: An Introduction to XAI

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Last updated on September 22, 2022 3:30 pm
SKU: 35168442

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This book takes an in-depth approach to presenting the fundamentals of explainable AI through mathematical theory and practical use cases. The content is split into five parts: 1) pre-hoc techniques involving exploratory data analysis, visualization and feature engineering, 2) intrinsic and interpretable machine learning, 3) model-agnostic methods, 4) explainable deep learning methods and 5) A survey of interpretable and explainable methods applied to time series, natural language processing and computer vision.
The field of Explainable AI addresses one of the most significant shortcomings of machine learning and deep learning algorithms today: the interpretability of models. As algorithms become more powerful and make predictions with better accuracy, it becomes increasingly important to understand how and why a prediction is made. Without interpretability and explainability, it would be difficult for the users to trust the predictions of real-life applications of AI.

Explainable Artificial Intelligence: AN Introduction to XAI offers its readers a collection of techniques and case studies that serves as an accessible introduction for those entering the field, and for current AI/ML researchers as they integrate explainability into their research and innovation.

Specification: Explainable Artificial Intelligence: An Introduction to XAI

Release date NZ

November 2nd, 2021

Author

Uday Kamath John Liu

Pages

392

Edition

1st ed. 2021

Audience

Professional & Vocational

Illustrations

161 Illustrations, color, 33 Illustrations, black and white, VIII, 392 p. 194 illus., 161 illus. in color.

Country of Publication

Switzerland

Imprint

Springer Nature Switzerland AG

Dimensions

165x220x25

ISBN-13

9783030833558

Product ID

35168442

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Explainable Artificial Intelligence: An Introduction to XAI
Explainable Artificial Intelligence: An Introduction to XAI

$207.01

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