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Explainable AI: Interpreting, Explaining and Visualizing Deep Learning (Paperback, 1st ed. 2019) Loot Price: R2,919
Discovery Miles 29 190
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning (Paperback, 1st ed. 2019): Wojciech Samek, Gregoire...

Explainable AI: Interpreting, Explaining and Visualizing Deep Learning (Paperback, 1st ed. 2019)

Wojciech Samek, Gregoire Montavon, Andrea Vedaldi, Lars Kai Hansen, Klaus-Robert Muller

Series: Lecture Notes in Computer Science, 11700

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Loot Price R2,919 Discovery Miles 29 190 | Repayment Terms: R274 pm x 12*

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The development of "intelligent" systems that can take decisions and perform autonomously might lead to faster and more consistent decisions. A limiting factor for a broader adoption of AI technology is the inherent risks that come with giving up human control and oversight to "intelligent" machines. For sensitive tasks involving critical infrastructures and affecting human well-being or health, it is crucial to limit the possibility of improper, non-robust and unsafe decisions and actions. Before deploying an AI system, we see a strong need to validate its behavior, and thus establish guarantees that it will continue to perform as expected when deployed in a real-world environment. In pursuit of that objective, ways for humans to verify the agreement between the AI decision structure and their own ground-truth knowledge have been explored. Explainable AI (XAI) has developed as a subfield of AI, focused on exposing complex AI models to humans in a systematic and interpretable manner. The 22 chapters included in this book provide a timely snapshot of algorithms, theory, and applications of interpretable and explainable AI and AI techniques that have been proposed recently reflecting the current discourse in this field and providing directions of future development. The book is organized in six parts: towards AI transparency; methods for interpreting AI systems; explaining the decisions of AI systems; evaluating interpretability and explanations; applications of explainable AI; and software for explainable AI.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Series: Lecture Notes in Computer Science, 11700
Release date: August 2019
First published: 2019
Editors: Wojciech Samek • Gregoire Montavon • Andrea Vedaldi • Lars Kai Hansen • Klaus-Robert Muller
Dimensions: 235 x 155 x 30mm (L x W x T)
Format: Paperback
Pages: 439
Edition: 1st ed. 2019
ISBN-13: 978-3-03-028953-9
Categories: Books > Computing & IT > General theory of computing > General
Books > Computing & IT > Computer communications & networking > Network security
Books > Computing & IT > Applications of computing > Artificial intelligence > General
Books > Computing & IT > Applications of computing > Image processing > General
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LSN: 3-03-028953-2
Barcode: 9783030289539

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