Bibliografía básica

• Los apuntes de clase que tomarán los estudiantes.
• Strogatz S.H., "Nonlinear dynamics and chaos" Addison-Wesley Publishing Company (1994).
• Dayan P. and L. Abbott, "Theoretical neuroscience: computational and mathematical modeling of neural systems", MIT Press (2001).
• T.M. Mitchell, "Machine Learning" McGraw-Hill (1997).
• J. Hertz, A. Krogh and R.G Palmer, "Introduction to the theory of neural computation", Santa Fe Institute (1991).
• Michael A. Nielsen, "Deep learning", Determination Press (2016).



Bibliografía complementaria

• Izhikevich E.M., "Dynamical systems in neuroscience: the geometry of excitability and bursting", MIT Press (2006).
• Rieke F., Warland D., de Tuyter van Steveninck R. and Bialek W., "Spikes: exploring the neural code", MIT Press (1999).
• MacKay D.J.C., "Information theory, inference and learning algorithms", Cambridge University Press, (2003).
• Hstie T., Tibshirani R. and Fiedman J, "The elements of statistical learning, data mining, inference and prediction", Springer Verlag (2001).
• Ian Goodfellow, Yoshua Bengio and Aaron Courveille, "Deep learning", MIT Press (2016)

Facultad de Matemática, Astronomía, Física y Computación

Universidad Nacional de Córdoba

Haya de la Torre esq. Medina Allende
Ciudad Universitaria
5000 Córdoba
Argentina
Email: francisco.tamarit@unc.edu.ar