Fr. 150.00

Machine Learning for Edge Computing - Frameworks, Patterns and Best Practices

English · Hardback

Shipping usually within 3 to 5 weeks

Description

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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.

List of contents










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.


About the author










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.


Summary

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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