Robert H. Chen, Chelsea Chen

Artificial Intelligence

An Introduction for the Inquisitive Reader

• Gebundenes Buch

Produktbeschreibung

Artificial Intelligence: An Introduction for the Inquisitive Reader guides readers through the history and development of AI, from its early mathematical beginnings through to the exciting possibilities of its potential future applications. To make this journey as accessible as possible, the authors build their narrative around accounts of some of the more popular and well-known demonstrations of artificial intelligence including Deep Blue, AlphaGo and even Texas Hold'em, followed by their historical background, so that AI can be seen as a natural development of mathematics and computer science. As the book moves forward, more technical descriptions are presented at a pace that should be suitable for all levels of readers, gradually building a broad and reasonably deep understanding and appreciation for the basic mathematics, physics, and computer science that is rapidly developing artificial intelligence as it is today.

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.

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Chapman & Hall/CRC Mathematics and Artificial Intelligence Series
• Verlag: Chapman and Hall/CRC / Taylor & Francis
• Seitenzahl: 344
• Erscheinungstermin: 9. Juni 2022
• Englisch
• Abmessung: 234mm x 156mm x 21mm
• Gewicht: 644g
• ISBN-13: 9781032103471
• ISBN-10: 1032103477
• Artikelnr.: 62953123

Autorenporträt

Robert H. Chen is the author of three books in English on Personal Computers, Liquid Crystal Displays, and Einstein's Relativity, and four books in Chinese on LCDs & Intellectual Property, Patents, Anglo-American Contract Law, and Technology & Copyright Law, and many scholarly articles in physics and the law. He has a Ph.D. in Space Physics and a J.D. in law and is a member of the California Bar. He divides his time between California and Taiwan with his wife and daughter. Chelsea C. Chen graduated in physics and computer science from U.C Berkeley and is a software development engineer at a major tech company in Silicon Valley. She presently lives in Northern California.

Inhaltsangabe

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

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1. Computing Hardware. 2. The Integrated Circuit. 3. Software. 4. Open
Source Software. 5. Expert Systems. 6. Inverted Decision Tree. 7. Deep
Blue. 8. Jeopardy and Miss Debater. 9. The Perceptron. 10.
Parameterization. 11. Gradient Descent and Backpropagation. 12. The
Cross-Entropy Cost Function. 13. Convolutional Neural Networks. 14.
Imagenet and Model Fitting. 15. Markov Chain Monte Carlo Simulation. 16.
Reinforcement Learning. 17. AlphaGo. 18. Game Theory. 19. Predictive
Analytics. 20. Support Vector Machines. 21. Top-Down Speech Recognition.
22. Bottom-Up Speech Recognition. 23. Speech Synthesis. 24. RBMs, GANs, and
LFCF. 25. LLMs and GPTs. 26. Massive Parallel Processing and Supercompuers.
27. Quantum Computing. 28. Industrial Robots: Robot Physicians. 29.
Autonomous Vehicles. 30. Exoplanets/Exomoon Astronomer. 31. Protein
Folding. 32. Intelligence. 33. The AI Singularity.