Description
Taylor and Francis Ltd Machine Learning for Edge Computing 1st Edition 2022 Hardbound by Singh, Amitoj
Introduces edge computing, hardware for edge computing AI, edge virtualization techniques _x000D_Explores edge intelligence and deep learning applications, training and optimization _x000D_Explains machine learning algorithms for edge _x000D_Reviews AI on IoT Discusses future edge computing needs_x000D_ _x000D_
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._x000D_