Neural networks and deep learning : a textbook / Charu C. Aggarwal.Material type: TextLanguage: English Publication details: Cham, Switzerland : Springer, 2018. Description: 1 online resource (xxiii, 497 pages) : illustrations (some color)ISBN: 9783319944630; 3319944630; 9783319944623Subject(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
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CUTN Central Library
This is a searchable open catalogue of all library of the Central University of Tamil Nadu.
|Non-fiction||006.32 AGG (Browse shelf(Opens below))||Checked out to Himanshu Kumar Himanshu Kumar (R201302)||19/08/2022||37494|
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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