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Neural networks and deep learning : a textbook / Charu C. Aggarwal.

By: Aggarwal, Charu C | [author.].
Material type: materialTypeLabelBookPublisher: Cham, Switzerland : Springer, 2018Description: 1 online resource (xxiii, 497 pages) : illustrations (some color).ISBN: 9783319944630; 3319944630; 9783319944623.Subject(s): Computer science | Neural networks (Computer science) | Machine learning | Computers | Computers | Computer networking & communications | Computer architecture & logic design | Artificial intelligence | Information systems | Computers | Artificial intelligence | -- Online Services -- General | -- Systems Architecture -- General | | | -- Intelligence (AI) & Semantics | Genre/Form: Electronic books.DDC classification: 006.32
Contents:
1 An Introduction to Neural Networks. 2 Machine Learning with Shallow Neural Networks. 3 Training Deep Neural Networks. 4 Teaching Deep Learners to Generalize. 5 Radical Basis Function Networks. 6 Restricted Boltzmann Machines. 7 Recurrent Neural Networks. 8 Convolutional Neural Networks. 9 Deep Reinforcement Learning. 10 Advanced Topics in Deep Learning.
Summary: This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, Read more...
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General Books General Books CUTN Central Library

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Generalia
Non-fiction 006.32 AGG (Browse shelf) Available 37494

Academic

1 An Introduction to Neural Networks. 2 Machine Learning with Shallow Neural Networks. 3 Training Deep Neural Networks. 4 Teaching Deep Learners to Generalize. 5 Radical Basis Function Networks. 6 Restricted Boltzmann Machines. 7 Recurrent Neural Networks. 8 Convolutional Neural Networks. 9 Deep Reinforcement Learning. 10 Advanced Topics in Deep Learning.


This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, Read more...

Includes bibliographical references and index.

Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK). UkOxU

Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force. UkOxU

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