Pro deep learning with TensorFlow 2.0 : (Record no. 13791)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02758cam a2200265 i 4500 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781484289310 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 1484289315 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781484289310 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781484289310 |
| DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | Q325.5 .P38 023 |
| MAIN ENTRY--AUTHOR NAME | |
| Personal name | Pattanayak, Santanu, |
| TITLE STATEMENT | |
| Title | Pro deep learning with TensorFlow 2.0 : |
| Remainder of title | a mathematical approach to advanced artificial intelligence in Python / |
| Statement of responsibility, etc | Santanu Pattanayak |
| EDITION STATEMENT | |
| Edition statement | Second edition |
| Copyright Date | |
| Place of publication | New York, NY : |
| Name of publisher | Apress, |
| Year of publication or production | [2023] |
| Copyright Date | |
| Year of publication or production | ©2023 |
| Place of publication | INDIA |
| Name of publisher | BANGLORE, KARMATAKA |
| PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource (667 pages) : |
| Other physical details | illustrations |
| SUMMARY, ETC. | |
| Summary, etc | This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0. Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you will learn about convolutional neural networks, including new convolutional methods such as dilated convolution, depth-wise separable convolution, and their implementation. You'll then gain an understanding of natural language processing in advanced network architectures such as transformers and various attention mechanisms relevant to natural language processing and neural networks in general. As you progress through the book, you'll explore unsupervised learning frameworks that reflect the current state of deep learning methods, such as autoencoders and variational autoencoders. The final chapter covers the advanced topic of generative adversarial networks and their variants, such as cycle consistency GANs and graph neural network techniques such as graph attention networks and GraphSAGE. Upon completing this book, you will understand the mathematical foundations and concepts of deep learning, and be able to use the prototypes demonstrated to build new deep learning applications. What You Will Learn Understand full-stack deep learning using TensorFlow 2.0 Gain an understanding of the mathematical foundations of deep learning Deploy complex deep learning solutions in production using TensorFlow 2.0 Understand generative adversarial networks, graph attention networks, and GraphSAGE Who This Book Is For: Data scientists and machine learning professionals, software developers, graduate students, and open source enthusiasts |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine learning. |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial intelligence. |
| ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://rave.ohiolink.edu/ebooks/ebc2/9781484289310 |
| ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://link.springer.com/10.1007/978-1-4842-8931-0 |
| ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://go.ohiolink.edu/goto?url=https://link.springer.com/10.1007/978-1-4842-8931-0 |
| ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://learning.oreilly.com/library/view/~/9781484289310/?ar |
| ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Library of Congress Classification |
| Koha item type | Books |
| Permanent Location | Current Location | Date acquired | Full call number | Accession Number | Koha item type |
|---|---|---|---|---|---|
| Gabriel Afolabi Ojo Central Library (Headquarters). | Gabriel Afolabi Ojo Central Library (Headquarters). | 11/04/2024 | Q325.5 .P38 2023 | 0194940 | Books |
| Gabriel Afolabi Ojo Central Library (Headquarters). | Gabriel Afolabi Ojo Central Library (Headquarters). | 11/04/2024 | Q325.5 .P38 2023 | 0194941 | Books |
| Gabriel Afolabi Ojo Central Library (Headquarters). | Gabriel Afolabi Ojo Central Library (Headquarters). | 11/04/2024 | Q325.5 .P38 2023 | 0194939 | Books |