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Explainable Deep Learning Ai : Methods and Challenges, Paperback by Benois-pi...

Description: Explainable Deep Learning Ai : Methods and Challenges, Paperback by Benois-pineau, Jenny (EDT); Bourqui, Romain (EDT); Petkovic, Dragutin (EDT); Quenot, Georges (EDT), ISBN 0323960987, ISBN-13 9780323960984, Like New Used, Free shipping in the US Explainable Deep Learning AI: Methods and Challenges presents the latest works of leading researchers in the XAI area, offering an overview of the XAI area, along with several novel technical methods and applications that address explainability challenges for deep learning AI systems. Th overviews XAI and then covers a number of specific technical works and approaches for deep learning, ranging from general XAI methods to specific XAI applications, and finally, with user-oriented evaluation approaches. It also explores the main categories of explainable AI – deep learning, which become the necessary condition in various applications of artificial intelligence. The groups of methods such as back-propagation and perturbation-based methods are explained, and the application to various kinds of data classification are presented. Provides an overview of main approaches to Explainable Artificial Intelligence (XAI) in the Deep Learning realm, including the most popular techniques and their use, concluding with challenges and exciting future directions of XAI Explores the latest developments in general XAI methods for Deep Learning Explains how XAI for Deep Learning is applied to various domains like images, medicine and natural language processing Provides an overview of how XAI systems are tested and evaluated, specially with real users, a critical need in XAI

Price: 123.51 USD

Location: Jessup, Maryland

End Time: 2024-11-03T19:27:23.000Z

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Explainable Deep Learning Ai : Methods and Challenges, Paperback by Benois-pi...

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Book Title: Explainable Deep Learning Ai : Methods and Challenges

Number of Pages: 395 Pages

Publication Name: Explainable Deep Learning Ai : Methods and Challenges

Language: English

Publisher: Elsevier Science & Technology

Publication Year: 2023

Subject: Expert Systems, Intelligence (Ai) & Semantics, General

Type: Textbook

Item Length: 9.2 in

Subject Area: Computers, Science

Author: Romain Bourqui

Item Width: 7.5 in

Format: Trade Paperback

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