liviu-

>Torrents don't really work for music

How come? I know What.CD closed down, but I remember that RuTracker had quite a large selection of high-fidelity music records.

Not at all: please check out /r/TrueFilm and /r/flicks.

I suspect he's referring to following HN and similar communities.

My understanding is that the grandparent comment was referring to _software_ engineers.

>Surprised SICP isn't in there.

I'm sure people are more likely to link to the actual SICP page [1] rather than the Amazon page, especially as it's free on the website. If the discussion was in the context of buying the book, I would personally still link the MIT Press page [2], rather than the Amazon page.

Searching for "https://mitpress.mit.edu/sicp/" on Algolia's HN search engine results in 72 hits [3].

----

[1] https://mitpress.mit.edu/sicp/

[2] https://mitpress.mit.edu/books/structure-and-interpretation-...

[3] https://hn.algolia.com/?query=https://mitpress.mit.edu/sicp/...

Ding has `--version`, and a help message too :P

To be honest, a big chunk of it is just handling user input and attempting to provide useful error messages.

Great point -- there's a pull request addressing this issue just now: https://github.com/liviu-/ding/pull/4

The "one-line" server is just multiple commands separated by ';' and joined into one line. At best a pointless exercise, and at worst a deceiving one.

projects ML?

Is there a name for this type of graph?

So the International Energy Agency predicts that by 2035 humans may disappear? What about more recent predictions?

>It doesn't depend on ImageMagick (a bonus in my book)

Why is it a bonus besides lowering the number of dependencies?

Especially given that HN offers no support for saving items other than upvoting.

I found it quite interesting to compare HN and /r/statistics in terms of the tone difference in the comments when discussing this article: https://www.reddit.com/r/statistics/comments/4fw1bn/sorry_ar...

> I quickly discovered that such a system was overkill for me, and resorted to using an open source implementation of a simpler algorithm [1].

Maybe worth pointing out that the "simpler algorithm" they used seems to be a cascading ensemble of adaptive boosting algorithms, technique similar to the ones used on Kaggle to win the big prizes. Maybe simpler than some neural nets in some ways, but nothing close to the simplicity of nearest neighbour search.

[1] http://docs.opencv.org/2.4/doc/tutorials/objdetect/cascade_c...

Both arithmetic mean and median are averages, so unless they specify what average they used for the annual income, you may only assume what the author meant.

EDIT: Never mind, the author also says:

>Moreover, we compare median annual values for software engineers with mean annual values for the general population

TL;DR from https://www.reddit.com/r/netsec/comments/4dvifg/im_not_a_hum... (though you may be overly-cautious as blackhat.com seems to be the webpage of a computer security conference [1]):

"""

Live attack To obtain an exact measurement of our attack’s accuracy, we run our automated captcha-breaker against reCaptcha. We employ the Clarifai service as it shows the best result amount other services.

Labelled dataset. We created a labelled dataset to exploit the image repetition. We manually labelled 3,000 images collected from challenges, and assigned each image a tag describing the content. We selected the appropriate tags from our hint list. We used pHash for the comparison, as it is very efficient, and allows our system to compare all the images from a challenge to our dataset in 3.3 seconds. We ran our captcha-breaking system against 2,235 captchas, and obtained a 70.78% accuracy. The higher accuracy compared to the simulated experiments is, at least partially, attributed to the image repetition; the history module located 1,515 sample images and 385 candidate images in our labelled dataset.

Average run time. Our attack is very efficient, with an average duration of 19.2 seconds per challenge. The most time consuming phase is running GRIS, consuming phase, as it searches for all the images in Google and processes the results, including the extraction of links that point to higher resolution versions of the images.

"""

[1] https://en.wikipedia.org/wiki/Black_Hat_Briefings

For anyone interested, Goodfellow is answering questions about the book at: https://www.reddit.com/r/MachineLearning/comments/4domnk/the...

Or just http://libgen.io/ for a more friendly URL.

Could you please elaborate for those unfamiliar with their community?

>It was noted that even in 9x9 Go, with a comparable branching factor to Chess, traditional Go programs are still no stronger than on big boards.

Are they not? MoGo beat pros of 9 Dan on 9x9 in 2011: https://www.lri.fr/~teytaud/mogo.html

> a good Masters degree will definitely leave a motivated and skilled student with a good advisor a master of his or her specific field.

I'm having trouble believing this.

In UK, most Masters degrees last 1 year, and there are several degrees considered good such as Imperial's MSc in Machine Learning, Cambridge's MPhil in Machine Learning, Speech and Language Technology, Edinburgh's MSc in Cognitive Science, and others. Is it really possible to become a "master" of machine learning in one year?

Also, at least in Computer Science, most of the Bachelors degrees considered good in UK do not seem to focus at all on replicating science. In fact, for my final year undergraduate project, I was encouraged to find something novel, and at no point my supervisor hinted towards focusing on replicability.

Is it perhaps more common in US?

Twitter does IM too: https://about.twitter.com/directmessages

>In those cases, I just messaged them back and told them to give the prize to someone else.