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Great textbook, I learned all the topology I know from it. Previously, Category Theory was taught as a field that connects branches of math, and thus in terms of other concepts. But recently there's a movement to view Category Theory as the definitive underlying field of math (instead of set theory), and teach different fields of math in terms of Category Theory rather than vice versa (a new-new math in a sense). I learned Category Theory well before learning abstract algebra and topology, and the embedding of Topology in Category Theory was seamless and intuitive; I feel as though this book proves that this new CT-centric view of math education has merit. One of the authors, Tai-Danae Bradley, also runs math3ma [1] and is a prominent figure in Applied Category Theory. I had the pleasure of hearing her talk, and her way of explaining abstractions is very easy to understand despite Category Theory being fairly obtuse at times (looking at you, Mac Lane!) Also, an obligatory shilling of the Topos Institute [2]. They're a research institution based in Berkeley, and they have weekly talks on Category Theory that they release on youtube. If you're interested in the categorification of mathematics, you need to check them out. [1] https://www.math3ma.com/ [2] https://topos.site/ |
Spoken like a true algebraist.
For anything related to stats, PDEs, and optimization (basically that subset if mathematics that is most useful to other sciences), category theory is a horrible foundation.
While it seems you can recover (with a looot of work) some existing theory, no sane researcher in these fields uses category theory.
And there is also no motivation to do so, since unlike for algebraic topology, algebra etc. the categorical viewpoint doesn't really make it clearer, what, e.g., the weak solution to a PDEs is, and why it coincidences (or not) with the classical solution.