[HN Gopher] Julia for Economists Bootcamp
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Julia for Economists Bootcamp
Author : sebg
Score : 53 points
Date : 2024-07-24 20:53 UTC (5 days ago)
(HTM) web link (github.com)
(TXT) w3m dump (github.com)
| hatmatrix wrote:
| There are some very useful rules of thumb here about when to use
| forward vs. reverse differentiation, etc. Very practical
| tutorial.
| photon_collider wrote:
| Has Julia's popularity in scientific computing and data science
| continued to grow? I haven't heard much about it recently.
| ysofunny wrote:
| isn't julia just another brand-name ((tm),(r), and (c)) python?
| like anaconda? or possibly the R language???
| frakt0x90 wrote:
| Not at all? Totally different programming paradigm and
| performance. Certain communities pull towards Julia a lot
| more than others. Mostly I've seen scientific fields that
| require HPC but don't want to do everything in FORTRAN and C.
| Paging Chris Rackauckas!
| ForHackernews wrote:
| No. It's not.
| jordanb wrote:
| R is an open source version of S, which was a competitor to
| SAS.
|
| Julia, from when I looked at it years ago was trying like a
| new version of Matlab or Mathematica. It was very linear-
| algebra focused, and were trying to replace those packages
| plus Fortran. They had some gimmicks like an IDE that would
| render mathematical notion like TeX for your matrices.
|
| Python wasn't the obvious "Fortran killer" scientific
| language it is today. In fact it's arguably really weird that
| Python ended up winning that segment. In any case, I think
| Julia's been struggling since its inception.
| minetest2048 wrote:
| Julia feels like a Matlab++ with its one based indexing and
| `function end` syntax Mojo is what you're thinking of
| ls612 wrote:
| I primarily use MATLAB and what stops me from using Julia
| is the package management.
|
| Also the VSCode extension has weird performance problems
| when trying to debug Julia code.
| cactusfrog wrote:
| I think it has correctness issues
| maximilianroos wrote:
| Source?
| minetest2048 wrote:
| https://yuri.is/not-julia/ HN discussion:
| https://news.ycombinator.com/item?id=31396861
| jarbus wrote:
| I use Julia regularly for experimental machine learning. It's
| great for writing high performance, distributed code and even
| easier than Python for this kind of work, since I can optimize
| the entire stack in a single language. Not sure if it's growing
| in popularity but it's really solid for what it does
| nextos wrote:
| Me too, and I'd like it to succeed. But the major problem
| right now is that it doesn't have anything that is close to
| Torch or JAX in performance _and_ robustness. Flux et al. are
| 90% there, but the last 10% requires a massive investment,
| and Julia doesn 't have any corporate juggernaut funding
| development.
|
| This is hurting Julia's adoption. The rest of the language is
| incredibly elegant, as there is no 2-language divide, like in
| Python. Furthermore, it is really performant. With very
| little effort one can write code that is within 2-1.5x of
| C++, often closer.
|
| One possibility is that something like Mojo takes Julia's
| spot. Mojo has some of the advantages of Julia, plus very
| tight integration with Python, its syntax and its ecosystem.
| I would still prefer Julia, but this is something to keep in
| mind.
| currymj wrote:
| certainly yes in scientific computing, less so in ML/data
| science. there's much of the culture of scientific computing in
| economics -- lot of heavy numerical stuff in addition to the
| statistical modeling you might expect.
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