Explainable Deep Learning AI

This book PDF is perfect for those who love Computers genre, written by Jenny Benois-Pineau and published by Elsevier which was released on 20 February 2023 with total hardcover pages 348. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Explainable Deep Learning AI books below.

Explainable Deep Learning AI
Author : Jenny Benois-Pineau
File Size : 40,7 Mb
Publisher : Elsevier
Language : English
Release Date : 20 February 2023
ISBN : 9780323993883
Pages : 348 pages
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Explainable Deep Learning AI by Jenny Benois-Pineau Book PDF Summary

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. The book 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

Explainable Deep Learning AI

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. The book overviews XAI and then covers a

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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

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