Engineering Mathematics and Artificial Intelligence : Foundations, Methods, and Applications (Paperback)

1. Multiobjective Optimization: An Overview.  2. Inverse Problems.  3. Decision Tree for Classification and Forecasting.  4. A Review of Choice Topics in Quantum Computing and Some Connections with Machine Learning.  5. Sparse Models for Machine Learning.  6. Interpretability in Machine Learning.  7. Big Data: Concepts, Techniques, and Considerations.  8. A Machine of Many Faces: On the Issue of Interface in Artificial Intelligence and Tools from User Experience.  9. Artificial Intelligence Technologies and Platforms.  10. Artificial Neural Networks.  11. Multicriteria Optimization in Deep Learning.  12. Natural Language Processing: Current Methods and Challenges.  13. AI and Imaging in Remote Sensing.  14. AI in Agriculture.  15. AI and Cancer Imaging.  16. AI in Ecommerce: From Amazon and TikTok, GPT-3 and LaMDA, to the Metaverse and Beyond.  17. The Difficulties of Clinical NLP.  18. Inclusive Green Growth in OECD Countries: Insight from The Lasso Regularization and Inferential Techniques.  19. Quality Assessment of Medical Images.  20. Securing Machine Learning Models: Notions and Open Issues.