TY  - BOOK
AU  - Singaram,Jayakumar
AU  - Iyengar,S.S.
AU  - Madni,Azad M.
ED  - SpringerLink (Online service)
TI  - Deep Learning Networks: Design, Development and Deployment 
SN  - 9783031392443
AV  - TK5101-5105.9 
PY  - 2024///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Telecommunication
KW  - Machine learning
KW  - Computational intelligence
KW  - Pattern recognition systems
KW  - Communications Engineering, Networks
KW  - Machine Learning
KW  - Computational Intelligence
KW  - Automated Pattern Recognition
N1  - Introduction -- Deep Learning -- Brief survey on Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) -- Tool Set for Deep Learning Applications -- Data-Set Design and Data Labeling -- DL Model: Design and Development -- Training and Testing of DL Model -- Deploying DL in Jetson Nano -- Deploying DL in Android Phone -- Deploying DL in Ultra96-V2 Field Programmable Gate Array (FPGA) -- Conclusion
N2  - This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-ranging conceptual modeling and programming tools that animate deep learning applications. The book is especially directed to students taking senior level undergraduate courses and to industry practitioners interested in learning about and applying deep learning methods to practical real-world problems. The unique features of this book are: Easy-to-understand description of the multiple facets of design, development and deployment of deep learning networks; Practical tools that facilitate understanding of underlying technology; Covers wide-ranging conceptual modeling and programming tools that animate deep learning applications
UR  - https://doi.org/10.1007/978-3-031-39244-3
ER  -