Machine Learning for Edge Computing (eBook, ePUB)

Frameworks, Patterns and Best Practices
Redaktion: Singh, Amitoj; Gandomani, Taghi Javdani; Kukreja, Vinay

• Format: ePub

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 200
• Erscheinungstermin: 29. Juli 2022
• Englisch
• ISBN-13: 9781000609240
• Artikelnr.: 64163020

Autorenporträt

Amitoj Singh is working as Assistant Professor in the department of Computational Sciences, MRSPTU, Bathinda, Punjab, India. Vinay Kukreja is working as an Associate professor at Chitkara University, Punjab, India. Taghi Javdani Gandomani is an Assistant Professor at Shahrekord University, Shahrekord, Iran.

Inhaltsangabe

1. Fog Computing And Its Security Challenges. 2. Machine Learning for Edge
Computing: Frameworks, Patterns and Best Practices. 3. Tea Vending Machine
from extracts of Natural Tea leaves and other ingredients: IoT and
Artificial Intelligence Enabled. 4. Recent Trends in OCR Systems: A Review.
5. A Novel Approach for Data Security using DNA Cryptography with
Artificial Bee Colony Algorithm in Cloud Computing. 6. Various Techniques
for Consensus Mechanism in Blockchain. 7. IoT inspired Smart Healthcare
Service for diagnosing remote patients with Diabetes. 8. Segmentation of
Deep Learning Models. 9. Alzheimer's disease Classification. 10. Deep
learning applications on Edge computing. 11. Designing an Efficient Network
based Intrusion Detection System using Artificial Bee Colony and ADASYN
oversampling approach.