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Deep learning architectures a mathematical approachUpplaga 1
- Upplaga: 1a upplagan
- Utgiven: 2020
- ISBN: 9783030367206
- Sidor: 760 st
- Förlag: Springer
- Format: Inbunden
- Språk: Engelska
Om boken
This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter.
This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.
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Mer om Deep learning architectures a mathematical approach (2020)
2020 släpptes boken Deep learning architectures a mathematical approach skriven av Ovidiu L. Calin. Det är den 1a upplagan av kursboken. Den är skriven på engelska och består av 760 sidor. Förlaget bakom boken är Springer.
Köp boken Deep learning architectures a mathematical approach på Studentapan och spara pengar.
Referera till Deep learning architectures a mathematical approach (Upplaga 1)
Harvard
Calin, O. L. (2020). Deep learning architectures a mathematical approach. 1:a uppl. Springer.
Oxford
Calin, Ovidiu L., Deep learning architectures a mathematical approach, 1 uppl. (Springer, 2020).
APA
Calin, O. L. (2020). Deep learning architectures a mathematical approach (1:a uppl.). Springer.
Vancouver
Calin OL. Deep learning architectures a mathematical approach. 1:a uppl. Springer; 2020.
