AI books
Course textbook
- Ian Goodfellow, Yoshua Bengio and Aaron Courville. Deep Learning. MIT Press, 2016. ISBN-13: 978-0262035613.
Supplements to textbook
Some books are not free (i.e, not on the open web), but are available for download when logged on to the UTSA library.
- Ch. C. Aggarwal, Neural Networks and Deep Learning, A Textbook. 2nd. ed. Springer, 2018. UTSA Library Download Link.
- M. P. Deisenroth, A. A. Faisal, Ch. S. Ong, Mathematics for Machine Learning, Cambridge University Press, 2020. ISBN: 9781108455145.
- L. Berlyand, P.-E. Jabin, Mathematics of Deep Learning, An Introduction to Foundational Mathematics of Neural Nets. 2nd. ed. Berlin, Boston: De Gruyter, 2026.
- B. Després, Neural networks and numerical analysis. Berlin: De Gruyter, 2022.
Other reference books
- Ch. C. Aggarwal, Artificial Intelligence, A Textbook. Springer, 2021. ISBN 978-3-030-72357-6 (eBook). UTSA Library Download Link
- R. S Sutton, A. G. Barto, Reinforcement Learning: An Introduction. 2nd. ed. MIT Press, 2018.
- P. Petersen, J. Zech, Mathematical Theory of Deep Learning.