Applied Learning Algorithms for Intelligent IoT

Herausgeber: Chelliah, Pethuru Raj; Nagarajan, Susila; Sakthivel, Usha

• Broschiertes Buch

Produktbeschreibung

Connectivity through the Internet of Things (IoT) processes and platforms combined with AI create the foundation of developing smart systems exhibiting intelligent behavior. The book illustrates promising and potential machine learning (ML) and deep learning (DL) algorithms through real-world and real-time business use cases.

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Produktdetails

• Verlag: Taylor & Francis Ltd (Sales)
• Seitenzahl: 356
• Erscheinungstermin: 4. Oktober 2024
• Englisch
• Abmessung: 234mm x 156mm x 20mm
• Gewicht: 517g
• ISBN-13: 9781032113210
• ISBN-10: 1032113219
• Artikelnr.: 71716018

Inhaltsangabe

1. Convolutional Neural Network in Computer Vision. 2. Trends and
Transition in the Machine Learning (ML) Space. 3. Deep Learning:
Algorithms, Platforms, Applications, and Research Trends in IoT. 4. The
Next-Generation IoT Use Cases across Industry Verticals using Machine and
Deep Learning Algorithms. 5. A Panoramic View of Cyber Attack Detection and
Prevention Using Machine Learning and Deep Learning Approaches. 6.
Regression Algorithms in Machine Learning. 7. Machine Learning Based
Industrial Internet of Things (IIoT) and Its Applications. 8. Employee
Turnover Prediction Using Single Voting Model. 9. A Novel Implementation of
Sentiment Analysis towards Data Science. 10. Conspectus of K-Means
Clustering Algorithm. 11. Systematic Approach to Deal with Internal
Fragmentation and Enhancing Memory Space during COVID-19. 12. IoT Automated
Spy Drone to Detect and Alert Illegal Drug Plants for Law Enforcement. 13.
Expounding K-Means-inspired Network Partitioning Algorithm for SDN
Controller Placement . 14. An Intelligent Deep Learning Based Wireless
Underground Sensor System for IoT Based Agricultural Application. 15.
Predicting Effectiveness of Solar Pond Heat Exchanger with LTES Containing
CUO Nanoparticle Using Machine Learning.