Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering

Non-linear dynamics and chaos by Strogatz https://www.stevenstrogatz.com/books/nonlinear-dynamics-and-... (https://www.stevenstrogatz.com/books/nonlinear-dynamics-and-chaos-with-applications-to-physics-biology-chemistry-and-engineering) I literally read it cover to cover like a novel

Strang's class is very pretty and excellent and just a little bit off from the center of the sorts of linear algebra used in machine learning. Not a lot off, but a little off. A field that does inspire a lot of deep learning folks and never gets mentiond in this sort of thing is the theory of physical dynamical systems. Attractor is a term that came from here, for example, and much of the mathematics behind the numerical fuckery behind deep nets is dynamical in nature. RNN's are entirely dynamical systems. Classic there is Strogatz book (https://www.amazon.com/Nonlinear-Dynamics-Chaos-Applications... (https://www.amazon.com/Nonlinear-Dynamics-Chaos-Applications-Nonlinearity/dp/0738204536)). There is also information theory, of course, which is part of the MacKay source.…