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Sheafification – The optimal path to mathematical mastery: The fast track (2022)

sheafification.com

21–30 of 53 posts

Re: Sheafification – The optimal path to mathematical mastery: The fast track (2022)

#21
post #3

The optimal path to mathematical mastery is "Error establishing a database connection"?

Computer science is math. Software engineering is not math.

And vibe-coding is barely coding, nevermind software engineering. (;

Re: Sheafification – The optimal path to mathematical mastery: The fast track (2022)

#22
post #15

This is wrong. In Computer Science language, human learning works in greedy way. We make locally optimal decisions in life. We cannot learn something in globally optimal way. We learn something in locally optimal way. And by repeating that we can reach somewhere at some point.

Here's my take on this - you should try to organize your local space of affordances and rewards in such a way that locally optimal choices will over time get you closer towards your global objective.

Re: Sheafification – The optimal path to mathematical mastery: The fast track (2022)

#23
post #19
post #18

Earlier quoted context omitted.

Shivlov for the one and only text in linear algebra is rough. IMO, it’s a little terse and fast paced. Efficient if you’re already well versed enough to be dangerous, but otherwise I think might slow down the beginner to a crawl in places. Same for Hartshorne’s Algebraic Geometry. Neither of these are bad textbooks at all, they both have a place on my bookshelf, but certainly better options have appeared through the…

What would you recommend as a supplement to Shilov's LA book?

Linear Algebra and Geometry by Igor Shafarevich, coupled with Linear Algebra by Friedberg, Insel, and Spence; the latter has great problems to work with, whereas the former is for a lucid exposition.

Re: Sheafification – The optimal path to mathematical mastery: The fast track (2022)

#24
post #15

This is wrong. In Computer Science language, human learning works in greedy way. We make locally optimal decisions in life. We cannot learn something in globally optimal way. We learn something in locally optimal way. And by repeating that we can reach somewhere at some point.

Here's my take on this - you should try to organize your local space of affordances and rewards in such a way that locally optimal choices will over time get you closer towards your global objective.

How can you ensure this if you don’t know where the global optimum is?

Re: Sheafification – The optimal path to mathematical mastery: The fast track (2022)

#26

Earlier quoted context omitted.

He probably doesn’t know how. This message is em from Wordpress. There are many WP providers where you just signup and start writing. They don’t tell you that if you get to HN front page, your db will die. I don’t know any static blog providers. He’d have to roll out his own or use Medium/Substack.

> I don’t know any static blog providers. Bear Blog comes to mind (no connection): https://bearblog.dev

That doesn't look static, it's a Django app, no?

Re: Sheafification – The optimal path to mathematical mastery: The fast track (2022)

#27
post #16

I am not sure if I agree with the list. I mean, one red flag is the frequent mention of Landau & Lifshitz. It is considered a "standard textbook", but I feel it stuck there by inertia. There are quite a few choices of both less boring and more insightful. (Back when I was reading such stuff, 20 years ago, the Feynman Lectures provided orders magnitude more insight. And fun.)

The Feynman Lectures are in a very different category from Landau & Lifshitz. You shouldn’t use L&L as your first university-level physics textbook (too difficult and divorced from the real world), but you probably shouldn’t use the FLP as your second, either, provided your first was good (too easy to be worth the time spent, though it’s still useful as pleasure reading that also fills in things you might have missed).

I have to admit I like the FLP less than the typical reader—it’s immensely fun in the moment, but I’ve always found the material too disjointed to build a coherent picture (ah, and now we have the tools to understand this random fun thing that I’ve never mentioned before and never going to mention after). As far as classic introductory books, the Berkeley course covers less, but the things it does cover fit together much better.

As for L&L, it’s just very uneven in quality. General relativity is great; electromagnetism is kind of bad. (And the two are in the same book!) Theoretical mechanics is adequate but way too much of a slog despite how short it is. Elasticity is surprisingly good. QM is OK but there’s a dozen approaches to QM depending on your background and it’s a toss-up whether this one will work for you. QED is good at the things it covers but like half of those things are relegated to the status of obscure specialist topics these days, while the point of view is something you should be aware of eventually but definitely not at your first go through the subject. And so on.

Re: Sheafification – The optimal path to mathematical mastery: The fast track (2022)

#29
There is no royal road to mathematics[1], and it's incredibly arrogant to think that any person can provide a single optimal path. For me for example the next steps are Axler, Abbott and Herstein[2]. That's where I am at the moment, and it's way earlier than the books listed here. It would be far from optimal for me to try to bang my head stubbornly on this list. Mathematics demands you put in the work to build a foundation - you cant just skip steps. For some people those books I listed are very rudimentary. For others they are definitely too advanced for where they are and they'll need something else.

Even more so is the idea that you can actually cover the material listed in that page in 3 years. If you were to blast through it in that time you would only be skimming the very surface of the topics. There's simply no way you could possibly do all of those subjects justice in that time.

[1] As Euclid is supposed to have said about geometry to the Pharoah Ptolemy when Ptolemy said he wanted to learn geometry but because of all the concerns of his kingdom he didn't have time to read the Elements.

[2] "Linear Algebra done Right" by Sheldon Axler

"Understanding Analysis" by Stephen Abbott

"Topics in Algebra" by Herstein. this is a lovely book and beautifully written but some of the notation is a bit dated. I have two more recent algebra books but they are a bit advanced for me until I work through Herstein. They are Aluffi "Algebra Chapter 0" which is a good modern algebra book which introduces category theory at the start and Hien I forget the title but it's a springer one that he claims is good for an introduction but it's definitely not. It assumes you know a lot. It's very good though.

Re: Sheafification – The optimal path to mathematical mastery: The fast track (2022)

#30
2-3 seems wildly optimistic for reading that list and actually consolidating the knowledge. During my math PhD I ready a fraction of that number of books. It’d be more convincing if someone was provided as an example of “mastering mathematics” (whatever that means) through this curriculum and timeframe.
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