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Type: BOOK - Published: 2021-12-15 - Publisher: Apress
Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black
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Type: BOOK - Published: 2021-04-28 - Publisher: Springer Nature
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches
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Type: BOOK - Published: 2020-07-31 - Publisher: Packt Publishing Ltd
Resolve the black box models in your AI applications to make them fair, trustworthy, and secure. Familiarize yourself with the basic principles and tools to dep
Language: en
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Type: BOOK - Published: 2022 - Publisher:
Learn the ins and outs of decisions, biases, and reliability of AI algorithms and how to make sense of these predictions. This book explores the so-called black
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Pages: 320
Type: BOOK - Published: 2020 - Publisher: Lulu.com
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simp