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This is great for working with python - https://github.com/gregsexton/ob-ipython

I haven't had as much luck using it for other languages, but I also haven't put in much effort into trying.


Thank you! I've been looking for this and didn't even realize. ob-julia is awful; really hope this can be made to work better. Also several obscure languages I've wanted to include snippets of in org that actually have Jupyter kernels...


Any suggestions for composing gantt charts in org mode? I've been using taskjuggler but printing them out to anything other than html (ex. image, pdf) has been a hassle.


I moved from dual booting mine to running Windows in a VM. I find it to be much more convenient and so far windows runs almost seamlessly (after upgrading to 32GB memory).


I strongly encourage using Julia for anyone applying mathematical optimization. It is (through JuMP[1], for example) one of the areas in which it really stands out.

[1] https://jump.readthedocs.io/en/latest/quickstart.html



Speaking of talks on Julia, I'll again recommend:

https://www.youtube.com/watch?v=dK3zRXhrFZY

"Julia: to Lisp or not to Lisp?" from the European Lisp Symposium in May 2016. I found it was rather illuminating on Julia in particular and lisps and programming languages in general.


The experiments were conducted on a 30 core Intel Xeon machine with 132 GB memory and 2 hyperthreads per core


But the "--master local[1]" setting they're using for Spark will run it on a single thread.

And, in the article they state "The algorithm took around 500 seconds to train on the NETFLIX dataset on a SINGLE processor, which is good for data as large as 1 billion ratings."

-emphasis mine


Being the one who conducted these experiments, I confirm that the number of threads was varied along(the graph shows performance scaling). I am sorry for the confusion caused, this was a typo, should have been "--master local[N]".


edit: local[1] has been updated to local[N], thank you for the update!

Ok thanks, I didn't know that's what "local[1]" did, so the more relevant comparison would be with --master local[30]?

The algorithm took around 500 seconds to train on the NETFLIX dataset on a SINGLE processor, which is good for data as large as 1 billion ratings. - this is from the sequential portion of the test, the parallel portion is the next section.


That was a typo in the blog post. If you look at the graph, with more cores, spark gets faster as does Julia. The typo is now fixed.


Thanks for the update. The typo had me misinterpreting things. Now it makes more sense.

Assuming you're part of the team? Keep up the good work.


We wanted to do this on a true distributed setup. However, all the largest datasets we could find where everyone has run ALS just fit on a single machine (even with lesser RAM than this one).


Probably meant "on a single machine".


Map command key to caps lock. Setting

(global-set-key (kbd "M-P") 'scroll-down-line)

(global-set-key (kbd "M-N") 'scroll-up-line)

Has also been indispensable for scrolling (though you may choose to do so differently, coming from vim).


Hear hear. Ctrl on caps lock changed my life. Then I bought a TECK^, which comes with a split spacebar and put left alt on caps (or where caps is usually, teck has control there) and right control on the right spacebar. This is honestly the best setup ever and I don't even use Emacs, I use Vim.

^ truly ergonomic computer keyboard. It's nice, but the hardware can be a bit wonky.


I forgot about that. Caps lock is useless 99% of the time and having that control available easily with your left pinky makes emacs (and everything else) work.

I'm so confused when I get on other people's computers and caps lock is actually caps lock.


Since he is looking at spacemacs, I'd recommend mapping caps lock to escape when it's tapped, but ctrl when it's pressed in conjunction with other keys. Very useful,

(though I suffer from the same problem when on other peoples computers)


I have been using Julia in emacs, primarily using ESS [1] and ob-julia [2] (org babel julia package). It is relatively well integrated with some basic auto-complete features and nice org-babel integration (as good as python or r).

[1] https://github.com/emacs-ess/ESS/wiki/Julia

[2] https://github.com/gjkerns/ob-julia


Cab service is bad inside Vancouver and utterly miserable outside Vancouver proper. If you are in the North shore, Burnaby, Tri-cities or further, you pretty much have to book a cab well in advance and then call in to remind them, and even then you may be better off just taking transit. Good luck getting anywhere in a reasonable amount of time with out a car.


Any idea why only 2 out of (seemingly) 4 assignments are posted? Are the other assignments available anywhere?


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