Ayush Somani,Alexander Horsch,Dilip K. Prasad
Interpretability in Deep Learning
Interpretability in Deep Learning
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- More about Interpretability in Deep Learning
Format: Paperback / softback
Length: 466 pages
Publication date: 02 May 2024
Publisher: Springer International Publishing AG
This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of deep learning models, with a focus on neural network architectures.
Dimension: 235 x 155 (mm)
ISBN-13: 9783031206412
Edition number: 2023 ed.
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