Self Studying the MIT Applied Math Curriculum
I did Strang's linear algebra course[0] (link goes to Youtube playlist of lectures) several years after graduating and recommend it highly. I was looking for refresher but I gained a deeper understanding of several important concepts; in particular it's fair to say I barely understood, or perhaps even misunderstood, SVD until Strang. If you're not sure if you need something like that, I suggest doing something like testing yourself on this video[1] or the MIT problem sets[2] it's easy to tell yourself that you "know" linear algebra when it would be closer to the truth to say that you <i>used</i> to know linear algebra, but can't answer even basic questions today. After Strang, Golub's book on Matrix Computations is also really incredible.[3]<p>[0]: <a href="https://www.youtube.com/watch?v=ZK3O402wf1c&list=PL49CF3715CB9EF31D" rel="nofollow">https://www.youtube.com/watch?v=ZK3O402wf1c&list=PL49CF3715C...</a><p>[1]: <a href="https://www.youtube.com/watch?v=Cll03FUxjuk" rel="nofollow">https://www.youtube.com/watch?v=Cll03FUxjuk</a><p>[2]: <a href="https://ocw.mit.edu/courses/mathematics/18-650-statistics-for-applications-fall-2016/assignments/" rel="nofollow">https://ocw.mit.edu/courses/mathematics/18-650-statistics-fo...</a><p>[3]: <a href="https://www.amazon.com/Computations-Hopkins-Studies-Mathematical-Sciences/dp/1421407949/ref=cm_cr_arp_d_product_top?ie=UTF8" rel="nofollow">https://www.amazon.com/Computations-Hopkins-Studies-Mathemat...</a>