optimali

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.

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

2016 talks are also up - http://juliacon.org

Overview - http://julialang.org/blog/2016/09/juliacon2016

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.

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

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).

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?

The library is still more sparse than other languages, but for implementing methods on your own there is no better alternative. Also for using existing libraries and functions, I found pycall to be very fast and easy to use.

I also used rcall a little and while not as nice as pycall was still simple to use and allowed access to any functionality I was interested in. I've heard good things about ccall/Cxx but haven't had a chance to use them yet.

http://julialang.org/teaching/ has some examples of where it is being used for teaching

https://www.youtube.com/watch?v=5muBxGQ9B2g is a nice introduction and overview

Thank you for the recommendation! Just ordered and excited for it to arrive.

That's great! Will be interesting to follow its support for multi-threading [1].

[1] https://github.com/JuliaLang/julia/pull/13410

It seems that though with in Julia, vectorized code is typically slower than non-vectorized, it is still faster than in R [1] / Python [2].

[1] http://www.johnmyleswhite.com/notebook/2013/12/22/the-relati...

[2] http://blog.rawrjustin.com/blog/2014/03/18/julia-vs-python-m...

Seems to go against their plan to stimulate research and innovation in industry.

Another article on this: http://betakit.com/how-will-the-ndps-tax-plan-affect-startup...

Cool. Have you found the MCMC approach to be less robust than clustering? It seems like this may be the case due to probability model assumptions.

Would be interesting to try and fit a distribution to error rates (some type of counting process) and then monitor the probability of having the occurred number of errors (with in some period of time). Then low probability events might indicate an outlier.