Bibliografía

Brunton, S. L., & Kutz, J. N. (2022). Data-driven science and engineering: Machine learning, dynamical systems, and control. Cambridge University Press.

Guckenheimer, J., & Holmes, P. (2013). Nonlinear oscillations, dynamical systems, and bifurcations of vector fields (Vol. 42). Springer Science & Business Media.

Goodfellow, Ian, Yoshua Bengio, Aaron Courville, and Yoshua Bengio. Deep learning. Vol. 1, no. 2. Cambridge: MIT press, 2016.

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. nature, 521(7553), 436-444.

Deep Learning with Python, Francois Chollet, Manning, 2018

Turbulence, coherent structures, dynamical systems and symmetry. Holmes, Philip, et al. Cambridge university press, 2012.

Differential equations, dynamical systems and an introduction to chaos, Hirsch M. W., Smale S. and Devaney R. L. Academic press, 2012

Dinámica No lineal, Gabriel Mindlin, Editorial UNQ, 2018

Artificial Intelligence: A Modern Approach (4th Edition, 2020)
Stuart Russell & Peter Norvig

Mathematics for Machine Learning (2022 paperback)
Marc Peter Deisenroth, A. Aldo Faisal & Cheng Soon Ong

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (3rd Edition, 2022)
Aurélien Géron

Grokking Deep Learning (2nd Edition, 2024)
Andrew Trask

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