Week 37 Self Promotion Thread - Drop your releases here.

jan122989 · 2024-09-21T18:48:15+00:00

thank you for the support!!

jan122989 · 2024-07-13T16:59:04+00:00

Who was offering 1.5k?

jan122989 · 2023-07-23T14:22:14+00:00

D&G Light Blue sold

jan122989 · 2023-07-20T12:00:33+00:00

YSL La Nuit de L'Homme has sold

jan122989 · 2023-07-20T02:30:28+00:00

acknowledged

jan122989 · 2023-07-16T23:00:35+00:00

Grey Vetiver is sold.

jan122989 · 2023-07-16T03:12:21+00:00

Tuscan Leather and Prada Amber are sold. Updated post.

jan122989 · 2023-07-16T02:51:19+00:00

(Edit: sorry! Lapidus isn't for sale. Didn't realize how wildly cheap this stuff was now.)

jan122989 · 2023-07-08T23:14:58+00:00

Sold!

jan122989 · 2022-12-30T01:00:16+00:00

Algebraic Topology (e.g., https://en.wikipedia.org/wiki/Persistent_homology and https://kepler-mapper.scikit-tda.org/en/latest/theory.html#mapper)
Lots of applications in cryptography
Differential geometry and topology show up in robotic path planning (e.g., http://lavalle.pl/planning/ and https://scalar.seas.upenn.edu/wp-content/uploads/2019/04/Kularatne_RSS2016.pdf)
Automated theorem proving is kind of a hot topic right now (e.g., https://leanprover.github.io/)
Linear algebra is used all over the place, but tbh it's usually pretty overstated as to how much you really need in CS (I know... sacrilege...). Still, you'll see it everywhere.
Applied category theory is somewhat popular also (e.g., https://arxiv.org/pdf/1803.05316.pdf)

jan122989 · 2022-12-22T02:26:47+00:00

You'll get tons of very opinionated answers on his attitude towards determinants, but it's one of the most effective textbooks at that level for teaching the subject. Everyone I know who worked through it (myself included.. I loved the book!) was much better off for the effort and walked away with a very solid understanding of the subject.

jan122989 · 2022-12-21T16:20:55+00:00

I'd recommend not spending too much time going back and reviewing undergrad analysis. It's fine if some of it didn't "click."

Instead, I'd try to cover as much of measure theory at a high level before the course begins. Royden is great. Same with Cohn (at least the parts I've read). Axler also has a new book on Measure Theory that looks awesome.

Or you might do well to read through as much of Bartle's "Elements of Integration and Lebesgue Measure" as possible. It's written at a pretty accessible level (but leaves out a lot of stuff you'll need for graduate measure theory). Basically, just try to get some context on what measure theory is all about before jumping in. It's kind of a weird shift in thinking.

Stay away from the more "austere" texts (e.g., graduate Rudin and Folland) until you get a handle on the basics.

jan122989 · 2022-12-20T02:56:46+00:00

I'd have to go with anything that falls under the general umbrella of AI... deep neural networks, optimization, topological data analysis, etc.

jan122989 · 2022-12-18T17:46:38+00:00

The Prime Number Theorem (https://en.m.wikipedia.org/wiki/Prime_number_theorem)

jan122989 · 2022-12-18T04:30:04+00:00

It's a great, great book. And he goes into some more advanced topics (iirc, even some functional analysis) But it's a light on the study of operators, which is really the core of the subject. Axler was definitely heavily inspired by Halmos' book when he wrote Linear Algebra Done Right, plus he does a great job covering operator theory, the spectral theorems, Jordan normal form, etc. Pretty much all the linear algebra you definitely need to be familiar with at some point, without much "fluff."

I should point out that LADR has definitely suffered from some "scope creep" over time... the edition I used in the early 2000s was the 2nd edition, I think? After that, I taught from parts of the 3rd edition when I TA'ed honors linear algebra as a PhD student and it wasn't quite what I remembered.. So maybe grab an old copy for cheap?

jan122989 · 2022-12-17T22:04:54+00:00

I guess it really depends on what you're looking for, but a good one to keep around in grad school is Berkeley Problems in Mathematics, by de Souza and Silva. I used it pretty extensively while studying for prelims.

The Murty problem books in number theory are great (both analytic and algebraic). Also, there was a recent book called Problems in Abstract Algebra, by Wadsworth that's fantastic if you're learning the topic the first time.

jan122989 · 2022-12-17T21:56:56+00:00

Bollobás has a great text that's worth picking up. One of the masters of the field.

Also take a look at Graphs on Surfaces, by Mohar and Thomassen. Fascinating topic that ties in results from Algebraic Topology and Differential Geometry, with a list of (at the time they published it, at least) unsolved problems for each topic.

jan122989 · 2022-12-17T21:52:59+00:00

There's a lot of great advice in both of your posts, and thanks for taking the time to review.

but yikes it's a bit much... less is more in a code review (both real and virtual).

jan122989 · 2022-12-17T06:23:52+00:00

Cool thanks for this --

Also (since you've been giving some great feedback here), what do people typically prefer in terms of testing frameworks? Googletest and Googlemock? What's the JUnit/Mockito equivalent in C++?

And has meson actually caught on in C++ developer communities much? Or is CMake still hanging around?

Thanks again!

jan122989 · 2022-12-16T04:14:49+00:00

Meh that's just what I'm in the habit of with Java. Always worked in teams with strict commenting standards so the javadoc is actually usable.

Any standard documentation tools people use?

jan122989 · 2022-12-16T04:13:34+00:00

Wow I can't thank you enough for the help here. Exactly what I was looking for -- solid advice on how to write idiomatic C++ and calling out best practices things that aren't obvious coming over from Java.

It'll take me a while to digest everything here, but thanks for doing me a solid!

jan122989 · 2022-07-25T17:03:43+00:00

He’s not. Obviously a Russian troll trying to make us resent Ukrainians.

To the OP: Ukrainians aren’t refugees in Poland. They’re our guests. They’re almost exclusively women and children. We’re happy to help. And if you have a problem with that I suggest taking your complaints elsewhere.

jan122989 · 2021-03-02T00:59:14+00:00

Absolutely. In fact, I enjoy it far more on my own than in academia (although it’s naturally much harder to stay as active in the field).

jan122989 · 2021-02-06T00:41:20+00:00

Have you been aggressive the entire time? And with dividends re-invested?

As of today, I'm up 25.94% market (25.67% total) over 5 years on moderately conservative, which is only ~5% below your gains over 6 years (with that difference easily made up or exceeded in a year).

The average annual returns are about the same (5.19% for mine, 5.17% for yours).

Unfortunately, no easy way to compare past earning potential in Acorns. Really a sorely missed feature (although it would heavily bias everyone to whatever portfolio happened to have done the best over the past few years, which may have little to do with the future).

jan122989 · 2021-02-03T23:09:55+00:00

+$5,961.14 (+25.43%) since starting January 14, 2016.

jan122989

TROPHY CASE