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Interpretability in Deep Learning - Dilip K. Prasad,Alexander Horsch,Ayush Somani

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2023-05-01
203,27 € 271,02 €

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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. The book can be used as a monograph on interpretability i ... Visas aprašymas

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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. The book can be used as a monograph on interpretability in deep learning covering the most recent topics as well as a textbook for graduate students. Scientists with research, development and application responsibilities benefit from its systematic exposition.

Daugiau informacijos

Autorius Dilip K. Prasad, Alexander Horsch, Ayush Somani
Leidėjas Springer Nature Switzerland
Išleidimo metai 2023
Viršelio tipas Kieti viršeliai
EAN 9783031206382
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203,27 € 271,02 €