jsrn
Joined 19 years ago
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911
Submissions
122
Member since
Feb 21
Recent submissions
Comment · 8 years ago
Does software count as an 'item' for you? If yes, for me (and I guess many others here) it would be various products of JetBrains, also Kotlin (even if I did not pay for that one directly) and OCR software from Abbyy. Also did not pay for, but use daily: nginx.
Comment · 10 years ago
Regarding this: "I wish Perl would do an inplace edit of a file without creating a backup, though."
$ perldoc perlrun
says:
> If no extension is supplied, and your system supports it, the original file is kept open without a name while the output is redirected to a new file with the original filename. When perl exits, cleanly or not, the original file is unlinked.
Which system are you using? With macOS and Linux, I get no automatic .bak extension when not providing a backup suffix, i.e. it behaves like you want under these systems.
Update: Apparently, anonymous files are not supported by Windows: http://stackoverflow.com/a/30539016 which would explain the behaviour you describe.
Comment · 10 years ago
Here is the command with jq instead of json_pp
$ curl -sS 'https://www.google.com/complete/search?client=hp&hl=en&xhr=t&q=aurora' | jq . | gsed -nE '/<\/?b>/{s```g;s`"|,|^ *``g;p}'
Comment · 10 years ago
Nice!
To run this with macOS, I had to use the GNU version of sed. I installed it with
$ brew install gnu-sed
As an avid Perl programmer, I had json_pp in my $PATH - for everyone else - it is here: https://metacpan.org/pod/JSON::PP
You can install it with cpanm:
$ cpanm JSON::PP
$ curl -L https://cpanmin.us | perl - App::cpanminus
$ curl -sS 'https://www.google.com/complete/search?client=hp&hl=en&xhr=t&q=aurora' \
| json_pp | gsed -nE '/<\/?b>/{s```g;s`"|,|^ *``g;p}'
$ function c() { curl -sS "https://www.google.com/complete/search?client=hp&hl=en&xhr=t&q=$1" | json_pp | gsed -nE '/<\/?b>/{s```g;s`"|,|^ *``g;p}'; }
$ c hacker
hacker news
hacker typer
hackerrank
hackerman
hackers movie
hacker fare
hackerone
hackers cast
hacker pschorr
$ c New+York
new york times
new york and company
new york giants
new york post
new york daily news
new york weatherComment · 10 years ago
Invented in 1998 by Perl hacker Abigail:
http://neilk.net/blog/2000/06/01/abigails-regex-to-test-for-...
(check out Abigail's other JAPHs if you like stuff like this)
Comment · 12 years ago
Regarding your (2.) - just to clarify this for others: With an enterprise provisioning profile, you can deploy your app to an arbitrary number of devices. These devices do not need to be known before via UDID (as with normal OTA provisioning). You can just upload the app to a server and ask people to download. So the devices do not technically have to belong to the same organization (even if this is perhaps Apple's intent). E.g., a friend of mine uses an enterprise account which they aquired for their university to deploy an app for a study (for data gathering). The subjects who install the app and enter their data are not all part of the university. Apple was informed about this use case and they did not have anything against it.
But, AFAIK Apple centrally checks the validity of the profile with each download and thus they are certainly able to detect if you use your enterprise profile to circumvent the appstore.
Comment · 13 years ago
Thanks, that makes sense.
So the parameter would be the number of slots (== number of input units of the deep NN).
And the transformation of the text into bag-of-words / n-grams would not be considered feature-engineering - or at least only 'low level feature engineering' - the higher level features will be learned by the deep network.
I guess one could go lower level still and even do away with bag-of-words / n-grams : limit the text size to e.g. 20000 characters, represent each character value with a numerical value (e.g. its ASCII code point when dealing with mainly English texts) and then simply feed this vector of codepoints to the input layer of the deep network. Given enough input data, it should learn location-invariant representations like bag-of-words / n-grams (or even better ones) itself, right?
Comment · 13 years ago
What would you use as input for the deep network?
I have only worked with text classification methods where I chose the features myself. As I understand it, a deep network still has (like a 'traditional'/non-deep ANN) a fixed number of inputs in its input layer, i.e. one would have to process each input text somehow before feeding it into the network (to make the input sizes equal). Is there a usual way to do this without doing feature-extraction?
Comment · 13 years ago
"Bokeh will be BSD/MIT."
Comment · 15 years ago
Point taken - what I primarily wanted to show is that the correct way is not much longer than the "looks like" solution. Yes, the Regexp is long, but it is nicely encapsulated in the Email::Valid module.
Comment · 15 years ago
> because those who can benefit from this kind of basic regexp examples are also those who will not understand the limitations.
I share your sentiment. The article is certainly useful for learning regexps. But IMHO it should also point to the correct way of doing things - often, the correct way is using a module and thus the resulting code is not much longer than the code in the article. For email address validation:
use Email::Valid;
print (Email::Valid->address('[email protected]') ? 'valid' : 'invalid');
perl -MEmail::Valid -E"say (Email::Valid->address('[email protected]') ? 'valid' : 'invalid');"
cpanm Email::Valid