An edition of Deep Learning
(2019)
Deep Learning
by John D. Kelleher
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An introduction to applying the age-old engineering principle “more is better” to neural-network models.
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Subjects
Machine learning, Artificial intelligence, neural networks, training algorithms, big data, backpropagationPeople
Geoffrey E. Hinton, Yann LeCunTimes
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Book Details
First Sentence
"Deep learning is the subfield of artificial intelligence that focuses on creating large neural network models that are capable of making accurate data-driven decisions."
Table of Contents
Contents
Series Foreword
Preface
Acknowledgments
1. Introduction to Deep Learning
2. Conceptual Foundations
3. Neural Networks: The Building Blocks of Deep Learning
4. A Brief History of Deep Learning
5. Convolutional and Recurrent Neural Networks
6. Learning Functions
7. The Future of Deep Learning
Glossary
Notes
References
Further Readings
Index
Edition Notes
Classifications
The Physical Object
Edition Identifiers
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History
- Created August 31, 2020
- 6 revisions
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| April 17, 2024 | Edited by ImportBot | import existing book |
| May 3, 2023 | Edited by frstndlstlns | added copyright |
| May 3, 2023 | Edited by frstndlstlns | Edited without comment. |
| May 3, 2023 | Edited by frstndlstlns | added description |
| August 31, 2020 | Created by ImportBot | Imported from Better World Books record |