Comment by ai_ia | Hacker News Reader

Comment by ai_ia | Hacker News Reader

The problem with these online resources are that you end up bookmarking them, but you are most likely never going to come back read them. Apologies, if I am generalising.

Learning something is not only reading the course content, that is one part of it (of course). But developing a robust and simple system where you can CRUD your mental model. If you got your note-taking thing figured out, technically you can learn and should be able to learn large amounts of material with sustained and relatively lesser effort. Once again, apologies for going on a tangent.

If anyone is looking to teach themselves CS along with CS Math, then we[1] are creating self-paced computer science courses. Our course content will be available as free online e-books [2] as well as their corresponding (paid) interactive versions and will be started getting released mid-November. We have two free courses as of now.

Although it doesn't start from scratch and we assume that you have got atleast highschool mathematics part covered.

[1]: https://primerlabs.io [2]: https://primerlabs.io/books

I actually find i'm the opposite (everyone is different of course - to each their own). I can learn from written resources fairly well once i get in the flow.

Interactive content or content where i have to do exercises a lot break my flow, because i am constantly switching gears.

Same here. For me the best flow comes from a simple information dense book, like any famous tome from Springer Graduate Texts in Mathematics.

In relation to this, IMHO the best way to learn the foundations of mathematics is to teach yourself either:

* Linear algebra and real analysis (if your end goal is ML or statistics)

* Logic and type theory (if your end goal is formal methods or PLT)

For the first option, a typical sequence (like the one taught at Harvard Math 55) is Halmos (or Axler) plus Rudin (and a good companion like Gelbaum & Olmsted). A more practical bottom-up approach is to use a good matrix analysis book such as Meyer, plus a more practical calculus (vs analysis) textbook like Hubbard & Hubbard.

For the second option, a good theoretical logic book (Ben Ari and Schoening are my favorites) paired along with Girard. A more practical option would use Huth & Ryan as a logic volume along with Pierce's TAPL.

Could you provide the full titles/authors of these books?

Full titles, authors and ISBNs should be available via Goodreads:

* Halmos: https://www.goodreads.com/book/show/692030

* Axler: https://www.goodreads.com/book/show/309768

* Rudin: https://www.goodreads.com/book/show/292079

* Gelbaum & Olmsted: https://www.goodreads.com/book/show/818070

* Meyer: https://www.goodreads.com/book/show/1002449

* Hubbard (5th edition available): https://www.goodreads.com/book/show/631871

* Ben Ari: https://www.goodreads.com/book/show/115121

* Schoening: https://www.goodreads.com/book/show/4993214

* Girard: https://www.goodreads.com/book/show/3400118

* Huth & Ryan: https://www.goodreads.com/book/show/151847

* Pierce: https://www.goodreads.com/book/show/112252

Amazing. Thank you.

I have been gravitating towards this. Feel like I only got very shallow learning from my CS courses. Bought physical books now to grok the subject better (for now theory of computation, algorithms etc).

Feel like especially my math foundation is lacking, so thanks a lot for these recommendations!

What's the onboarding page[1] using to determine the user's first name? It knew my first name the first time I opened it.

[1] https://app.primerlabs.io/onboarding

Google Sign In i'd wager

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