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.

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.