| 000 -LEADER |
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| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
231024b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781108835084 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.31 |
| Item number |
DRO |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Drori, Iddo |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Science of deep learning |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc |
Cambridge University Press, |
| Date of publication, distribution, etc |
2023 |
| Place of publication, distribution, etc |
Cambridge : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxii, 338 p. ; |
| Other physical details |
ill., map, |
| Dimensions |
26 cm. |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
44.99 |
| Price type code |
GBP |
| Unit of pricing |
107.60 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Deep learning |
|
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| Topical term or geographic name as entry element |
Machine learning |
|
|---|
| Topical term or geographic name as entry element |
Artificial Intelligence |
|
|---|
| Topical term or geographic name as entry element |
Computer Vision |
|
|---|
| Topical term or geographic name as entry element |
Transformers |
|
|---|
| Topical term or geographic name as entry element |
Graph neural networks |
|
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| Topical term or geographic name as entry element |
Variational autoencoders |
|
|---|
| Topical term or geographic name as entry element |
Deep reinforement |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |