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

By: Material type: TextTextLanguage: English Publication details: Cham, Switzerland : Springer, 2018.Description: 1 online resource (xxiii, 497 pages) : illustrations (some color)ISBN:
  • 9783319944630
  • 3319944630
  • 9783319944623
Subject(s): Genre/Form: DDC classification:
  • 006.32 23 AGG
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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Holdings
Item type Current library Collection Call number Status Date due Barcode
General Books General Books CUTN Central Library Generalia Non-fiction 006.32 AGG (Browse shelf(Opens below)) 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.

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