Description
Taylor and Francis Ltd Artificial Intelligence 1st Edition 2022 Hardbound by Chen, Robert H.
Features Only mathematical prerequisite is an elementary knowledge of calculusAccessible to anyone with an interest in AI and its mathematics and computer scienceSuitable as a supplementary reading for a course in AI or the History of Mathematics and Computer Science in regard to artificial intelligence. PART I: The Arrival of AI in the Human World. 1. Game-Playing. 2. Working Machines. 3. Intelligence. 4. The AI Singularity. PART II: The Artificial Intelligence Infrastructure. 5. Hardware. 6. Software. 7. Computer Communications. 8. Open Source Software. PART III: From Top to Bottom. 9. Top-Down Artificial Intelligence. 10. Bottom-Up Artificial Intelligence. 11. Machine Learning Modeling. 12. Markov Chain Monte Carlo Simulation. PART IV: Structure and Operation. 13. Artificial Neural Networks. 14. Pattern Recognition. 15. Parameterization. 16. Gradient Descent. 17. Backpropagation. 18. Convolutional Neural Networks. PART V: Progression. 19. The Cross-Entropy Cost Function. 20. Hyperparameterization. 21. Big Data. 22. Massively Parallel Processing. PART VI: Powers of Prediction. 23. Predictive Analytics. 24. Restricted Boltzmann Machine. 25. Latent Factors in Collaborative Filtering. 26. Support Vector Machines. 27. Reinforcement Learning. 28. AlphaGo and AlphaStar. 29. Game Theory. PART VII: Natural Language Processing. 30. Top-Down Speech Recognition. 31. Bottom-Up Speech Recognition. 32. Speech Synthesis. PART VIII: The Robotworld. 33. Robots at Work. 34. The Robot Millennial. 35. The Robot Future