- We will send in 10–14 business days.
/images/books/2819702/9780128167182.jpg)
- Publisher: Academic Press
- ISBN-10: 0128167181
- ISBN-13: 9780128167182
- Format: 19.1 x 23.5 x 1.5 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Deep Learning and Parallel Computing Environment for Bioengineering Systems (e-book) (used book) | bookbook.eu
Reviews
Description
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 18d.03:11:28
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Publisher: Academic Press
- ISBN-10: 0128167181
- ISBN-13: 9780128167182
- Format: 19.1 x 23.5 x 1.5 cm, softcover
- Language: English English
Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas.
Reviews