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Interpretability in Deep Learning PDF

483 Pages·2023·11.133 MB·English
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Description:
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. In addition, it includes several case studies from application-oriented articles in the fields of computer vision, optics and machine learning related topic.
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Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.