Deep learning for engineers / Tariq M. Arif, Md Adilur Rahim.
| Author/creator | Arif, Tariq M. |
| Format | Electronic |
| Edition | First edition. |
| Publication Info | Boca Raton : CRC Press, Taylor & Francis Group, 2024. |
| Description | 1 online resource |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Subjects |
| Abstract | "Deep Learning for Engineers introduces fundamental principles of deep learning along with the explanation of basic elements required for understanding and applying deep learning models. As a comprehensive guideline for applying deep learning models in practical settings, this book features an easy-to-understand coding structure using Python and PyTorch with an in-depth explanation of four typical deep learning case studies on image classification, object detection, semantic segmentation, and image captioning. The fundamentals of Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) architectures and their practical implementations in science and engineering are also discussed"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Source of description | Description based on print version record and CIP data provided by publisher. |
| Genre/form | Electronic books. |
| LCCN | 2023040220 |
| ISBN | 9781003849827 epub |
| ISBN | 9781003402923 ebook |
| ISBN | paperback |
| ISBN | hardback |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |