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Recurrent Neural Networks
- From Simple to Gated Architectures
Engelsk Paperback
Recurrent Neural Networks
- From Simple to Gated Architectures
Engelsk Paperback

478 kr
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Om denne bog

This textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from scratch. It provides a treatment of the general recurrent neural networks with principled methods for training that render the (generalized) backpropagation through time (BPTT).  This author focuses on the basics and nuances of recurrent neural networks, providing technical and principled treatment of the subject, with a view toward using coding and deep learning computational frameworks, e.g., Python and Tensorflow-Keras. Recurrent neural networks are treated holistically from simple to gated architectures, adopting the technical machinery of adaptive non-convex optimization with dynamic constraints to leverage its systematic power in organizing the learning and training processes. This permits the flow of concepts and techniques that provide grounded support for design and training choices. The author''s approach enables strategic co-training of output layers, using supervised learning, and hidden layers, using unsupervised learning, to generate more efficient internal representations and accuracy performance. As a result, readers will be enabled to create designs tailoring proficient procedures for recurrent neural networks in their targeted applications.

Product detaljer
Sprog:
Engelsk
Sider:
121
ISBN-13:
9783030899318
Indbinding:
Paperback
Udgave:
ISBN-10:
3030899314
Udg. Dato:
5 jan 2023
Længde:
0mm
Bredde:
155mm
Højde:
235mm
Forlag:
Springer Nature Switzerland AG
Oplagsdato:
5 jan 2023
Forfatter(e):
Books from the same author
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