Applied Learning Algorithms for Intelligent IoT
portes grátis
Applied Learning Algorithms for Intelligent IoT
Sakthivel, Usha; Nagarajan, Susila; Chelliah, Pethuru Raj
Taylor & Francis Ltd
10/2024
356
Mole
9781032113210
Pré-lançamento - envio 15 a 20 dias após a sua edição
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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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
RGB Model;Gradient Boosting Decision Tree;RGB Color Model;IoT Device;Random Forest;Ml Algorithm;RFID Tag;Clustering Algorithm;SP;Support Vector Machine;Unsupervised Learning;Data Set;SA Algorithm;NB;CNN Architecture;Digital Twin;Malware Detection;API Call;CuO Nanoparticles;Support Vector Regression;SVM Algorithm;Decision Tree Regression;Convolution Layer;STT;Naive Bayes Classification
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
RGB Model;Gradient Boosting Decision Tree;RGB Color Model;IoT Device;Random Forest;Ml Algorithm;RFID Tag;Clustering Algorithm;SP;Support Vector Machine;Unsupervised Learning;Data Set;SA Algorithm;NB;CNN Architecture;Digital Twin;Malware Detection;API Call;CuO Nanoparticles;Support Vector Regression;SVM Algorithm;Decision Tree Regression;Convolution Layer;STT;Naive Bayes Classification
