Deep Learning Models A Practical Approach for Hands-On Professionals /
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...
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| Format: | Électronique eBook |
| Langue: | anglais |
| Publié: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2024.
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| Édition: | 1st ed. 2024. |
| Collection: | Transactions on Computer Systems and Networks,
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| Sujets: | |
| Accès en ligne: | https://doi.org/10.1007/978-981-99-9672-8 |
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| 100 | 1 | |a Gamba, Jonah. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Deep Learning Models |h [electronic resource] : |b A Practical Approach for Hands-On Professionals / |c by Jonah Gamba. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Singapore : |b Springer Nature Singapore : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (XIV, 201 p. 265 illus.). |b 164 illus. in color. | ||
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| 490 | 1 | |a Transactions on Computer Systems and Networks, |x 2730-7492 | |
| 505 | 0 | |a 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 | |a 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. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
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