Machine learning for edge computing : frameworks, patterns and best practices /
Machine learning for edge computing : frameworks, patterns and best practices /
edited by Amitoj Singh, Vinay Kukreja, Taghi Javdani Gandomani.
- First edition.
- 1 online resource
Fog Computing And Its Security Challenges / Kamali Gupta, Deepali Gupta, Vinay Kukreja, Vipul Kaushik -- Machine Learning for Edge Computing : Frameworks, Patterns and Best Practices / Veerpal Kaur, Rajpal Kaur -- Tea Vending Machine from extracts of Natural Tea leaves and other -- Ingredients : IoT and Artificial Intelligence Enabled / Neha Sharma, Ram Kumar Ketti Ramachandran, Huma Naz, Rishabh Sharma -- Recent Trends in OCR Systems : A Review / Aditi Moudgil, Saravjeet Singh, Vinay Gautam -- A Novel Approach for Data Security using DNA Cryptography with Artificial Bee Colony Algorithm in Cloud Computing / Manisha Rani, Madhvi Popli, Gagandeep -- Various Techniques for Consensus Mechanism in Blockchain / Shivani Wadhwa, Gagandeep -- IoT inspired Smart Healthcare Service for diagnosing remote patients with Diabetes / Huma Naz, Rishabh Sharma, Neha Sharma, Sachin Ahuja -- Segmentation of Deep Learning Models / Prabhjot Kaur, Anand Muni Mishra -- Alzheimer's disease Classification / M. Sethi, S. Ahuja, V. Kukreja -- Deep learning applications on Edge computing / Naresh Kumar Trivedi, Abhineet Anand, Umesh Kumar Lilhore, Kalpna Guleria -- Designing an Efficient Network based Intrusion Detection System using Artificial Bee Colony and ADASYN oversampling approach / Manisha Rani, Gunreet Kaur, Gagandeep.
"This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it also discusses how to build AI models, i.e., model training and inference, on edge"--
9781003143468 1003143466 9781000609240 1000609243 9781000609233 1000609235
10.1201/9781003143468 doi
Edge computing.
Machine learning.
Cloud computing.
COMPUTERS / General
COMPUTERS / Machine Theory
COMPUTERS / Computer Engineering
R859.7.A78
610.285
Fog Computing And Its Security Challenges / Kamali Gupta, Deepali Gupta, Vinay Kukreja, Vipul Kaushik -- Machine Learning for Edge Computing : Frameworks, Patterns and Best Practices / Veerpal Kaur, Rajpal Kaur -- Tea Vending Machine from extracts of Natural Tea leaves and other -- Ingredients : IoT and Artificial Intelligence Enabled / Neha Sharma, Ram Kumar Ketti Ramachandran, Huma Naz, Rishabh Sharma -- Recent Trends in OCR Systems : A Review / Aditi Moudgil, Saravjeet Singh, Vinay Gautam -- A Novel Approach for Data Security using DNA Cryptography with Artificial Bee Colony Algorithm in Cloud Computing / Manisha Rani, Madhvi Popli, Gagandeep -- Various Techniques for Consensus Mechanism in Blockchain / Shivani Wadhwa, Gagandeep -- IoT inspired Smart Healthcare Service for diagnosing remote patients with Diabetes / Huma Naz, Rishabh Sharma, Neha Sharma, Sachin Ahuja -- Segmentation of Deep Learning Models / Prabhjot Kaur, Anand Muni Mishra -- Alzheimer's disease Classification / M. Sethi, S. Ahuja, V. Kukreja -- Deep learning applications on Edge computing / Naresh Kumar Trivedi, Abhineet Anand, Umesh Kumar Lilhore, Kalpna Guleria -- Designing an Efficient Network based Intrusion Detection System using Artificial Bee Colony and ADASYN oversampling approach / Manisha Rani, Gunreet Kaur, Gagandeep.
"This book divides edge intelligence into AI for edge (intelligence-enabled edge computing) and AI on edge (artificial intelligence on edge). It focuses on providing optimal solutions to the key concerns in edge computing through effective AI technologies, and it also discusses how to build AI models, i.e., model training and inference, on edge"--
9781003143468 1003143466 9781000609240 1000609243 9781000609233 1000609235
10.1201/9781003143468 doi
Edge computing.
Machine learning.
Cloud computing.
COMPUTERS / General
COMPUTERS / Machine Theory
COMPUTERS / Computer Engineering
R859.7.A78
610.285