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Artificial Intelligence and Machine Learning for EDGE Computing
Examines the methods and applications of Artificial Intelligence and Machine Learning as applied to Edge computing
Rajiv Pandey (Edited by), Sunil Kumar Khatri (Edited by), Neeraj Kumar Singh (Edited by), Parul Verma (Edited by)
9780128240540
Paperback, published 26 April 2022
516 pages
23.5 x 19 x 3.2 cm, 0.45 kg
Approx.490 pages
Part 1: AI and Machine Learning 1. Artificial Intelligence 2. Machine Learning 3. Regression Analysis 4. Bayesian Statistics 5. Learning Theory 6. Supervised Learning 7. Unsupervised Learning 8. Reinforcement Learning 9. Instance Based Learning and Feature Engineering Part 2: Data Science and Predictive Analysis 10. Introduction to Data Science and Analysis 11. Linear Algebra, Statistics, Probability, Hypothesis and Inference, Gradient Descent 12. Predictive Analysis Part 3: Edge Computing 13. Distributed Computing - Cloud to fog to Edge 14. Edge Computing 15. Integrating AI with Edge Computing 16. Machine learning integration with Edge Computing 17. Applying AI/Ml at the edge
Subject Areas: Biomedical engineering [MQW]