Deep Learning Models (Record no. 87820)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04444nam a22005775i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-981-99-9672-8 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730171810.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240409s2024 si | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9789819996728 |
| -- | 978-981-99-9672-8 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 005.3 |
| 100 1# - AUTHOR NAME | |
| Author | Gamba, Jonah. |
| 245 10 - TITLE STATEMENT | |
| Title | Deep Learning Models |
| Sub Title | A Practical Approach for Hands-On Professionals / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XIV, 201 p. 265 illus., 164 illus. in color. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Transactions on Computer Systems and Networks, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Chapter 1. Basic Approaches in Object Detection and Classification by Deep Learning -- Chapter 2. Requirements for Hands-on Approach to Deep Learning -- Chapter 3. Building Deep Learning Models -- Chapter 4. The Building Blocks of Machine Learning and Deep Learning -- Chapter 5. Remote Sensing Example for Deep Learning. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book focuses on and prioritizes a practical approach, minimizing theoretical concepts to deliver algorithms effectively. With deep learning emerging as a vibrant field of research and development in numerous industrial applications, there is a pressing need for accessible resources that provide comprehensive examples and quick guidance. Unfortunately, many existing books on the market tend to emphasize theoretical aspects, leaving newcomers scrambling for practical guidance. This book takes a different approach by focusing on practicality while keeping theoretical concepts to a necessary minimum. The book begins by laying a foundation of basic information on deep learning, gradually delving into the subject matter to explain and illustrate the limitations of existing algorithms. A dedicated chapter is allocated to evaluating the performance of multiple algorithms on specific datasets, highlighting techniques and strategies that can address real-world challenges when deep learning is employed. By consolidating all necessary information into a single resource, readers can bypass the hassle of scouring scattered online sources, gaining a one-stop solution to dive into deep learning for object detection and classification. To facilitate understanding, the book employs a rich array of illustrations, figures, tables, and code snippets. Comprehensive code examples are provided, empowering readers to grasp concepts quickly and develop practical solutions. The book covers essential methods and tools, ensuring a complete and comprehensive coverage that enables professionals to implement deep learning algorithms swiftly and effectively. This book is designed to equip professionals with the necessary skills to thrive in the active field of deep learning, where it has the potential to revolutionize traditional problem-solving approaches. This book serves as a practical companion, enabling readers to grasp concepts swiftly and embark on building practical solutions. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-981-99-9672-8 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Singapore : |
| -- | Springer Nature Singapore : |
| -- | Imprint: Springer, |
| -- | 2024. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
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| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Application software. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer networks . |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer vision. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer and Information Systems Applications. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Engineering and Networks. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Vision. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Science. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 2730-7492 |
| 912 ## - | |
| -- | ZDB-2-SCS |
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| -- | ZDB-2-SXCS |
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