Pierre Baldi (Irvine University of California)

Deep Learning in Science

• Gebundenes Buch

Produktbeschreibung

This is the first rigorous, self-contained treatment of the theory of deep learning. Aimed at scientists, instructors, and students interested in artificial intelligence and deep learning, it demonstrates many applications in physics, chemistry, and biomedicine. It includes a full set of exercises and encourages out-of-the-box thinking.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 450
• Erscheinungstermin: 1. Juli 2021
• Englisch
• Abmessung: 250mm x 174mm x 23mm
• Gewicht: 912g
• ISBN-13: 9781108845359
• ISBN-10: 1108845355
• Artikelnr.: 60743192

Autorenporträt

Pierre Baldi is Distinguished Professor of Computer Science at University of California, Irvine. His main research interest is understanding intelligence in brains and machines. He has made seminal contributions to the theory of deep learning and its applications to the natural sciences, and has written four other books.

Inhaltsangabe

1. Introduction
2. Basic Concepts
3. Shallow Networks and Shallow Learning
4. Two-Layer Networks and Universal Approximation
5. Autoencoders
6. Deep Networks and Backpropagation
7. The Local Learning Principle
8. The Deep Learning Channel
9. Recurrent Networks
10. Recursive Networks
11. Applications in Physics
12. Applications in Chemistry
13. Applications in Biology and Medicine
14. Conclusion
Appendix A. Reinforcement Learning and Deep Reinforcement Learning
Appendix B. Hints and Remarks for Selected Exercises
References
Index.