Earlier quoted context omitted.
It's a 100% static site, but Apache is still struggling :(. Should have used a bigger droplet...Sorry!
Turn off KeepAlive, if it's on.
Bad advice. That's likely to make it a lot worse.
Prodigy: A new tool for radically efficient machine teaching
61–70 of 75 posts
Re: Prodigy: A new tool for radically efficient machine teaching
#62I don't think (some) people understand; a slick data annotation tool like this is vastly more useful than the 20th variant of GAN that DeepMind produces :)
Totally agree. Annotation effort can explode out of control if you don't have good tooling. Well done, Explosion!
Re: Prodigy: A new tool for radically efficient machine teaching
#63I've been pulling my hair out and losing sleep over a specific problem I need to solve for a client. This tool, along with the linked spaCy lib have not only reduced the complexity of the task to be manageable, have also drastically reduced the projected completion time. In other words, Holy shit thank you OP.
Re: Prodigy: A new tool for radically efficient machine teaching
#64Wow, been a while since I've touched UX this good, loved the themes, is this open source?
Re: Prodigy: A new tool for radically efficient machine teaching
#65Looks promising and definitely a needed tool. I signed up for the beta and I used the demo version and have a couple of thoughts. 1. This seems closer to a reinforcement learning system than a pure annotation system. That seems to be by design, however based on the demo, I am not able to change or add to the annotations as I go, which is a big limitation. It's just yes, no (no feedback), ignore and undo. This is in c…
Thanks for the engaging questions! Reading between the lines, I think there's an important point that hasn't come across. Prodigy isn't SaaS --- it's a library you download and run. You can extend and customise every aspect of it, and there's definitely no lock-in. The model (and annotations) never have to leave your servers. For the specific questions: 1. The built-in web views all have binary annotation interfaces.…
I think there's an important point that hasn't come across. Prodigy isn't SaaS --- it's a library you download and run.
You're right, I totally missed that. Re-reading that comes through but it is definitely different than what I would have expected.
Thanks for the response, I'll dig in further.
Re: Prodigy: A new tool for radically efficient machine teaching
#66How many languages are supported? I see many more languages in Google's Syntaxnet library. What's keeping you from having the same list of 40 languages for POS tagging?
https://github.com/tensorflow/models/blob/master/syntaxnet/g...
Re: Prodigy: A new tool for radically efficient machine teaching
#67That's a nice UX but the flurry of initial upvotes on this looks kinda fishy, especially given that it's just annotation software.
I'm a data scientist and getting annotations for our data is one of our most onerous issues. I upvoted this. If it works well, I could see myself using it all the time. Making a model that gets you most of the way there is the easy part; getting clean, annotated data. Uggh.
Yep agreed, we've had to build similar things internally.
Getting labelled data is a pain.
Re: Prodigy: A new tool for radically efficient machine teaching
#68Earlier quoted context omitted.
> spaCY, the leading open-source NLP tool? Sounds like marketing BS. what about OpenNLP and Stanford's for NLP?
spaCY, the leading open-source NLP tool? Agreed, the description is definitely cringe-worthy. As if whoever wrote that wasn't aware that these are language geeks they're marketing to.
> spaCY, the leading open-source NLP tool?
* only supports 3 languages, though
Re: Prodigy: A new tool for radically efficient machine teaching
#69Earlier quoted context omitted.
I have an NLP bot as a hobby, but use old-fashioned statistics instead of ML. It looks like annotations here mean manually training the bot by seeding the learning data with hints.
A utility for labeling training data for supervised learning then?
Yes, with a bit of a twist. As I understand it, it'll keep retraining the model and asking you to label the examples it's least sure about. This is a lot faster and better than randomly labelling your data or trying to do it all.
Re: Prodigy: A new tool for radically efficient machine teaching
#70How many languages are supported? I see many more languages in Google's Syntaxnet library. What's keeping you from having the same list of 40 languages for POS tagging? https://github.com/tensorflow/models/blob/master/syntaxnet/g...
The UD treebanks have made it very easy to offer lots POS and dependency parsing models under a CC-by-NC license. We'll be putting up more of these for download as spaCy 2 stabilises.
We're mostly worried about saying we "support" a language when we've just trained a tagger on a UD treebank, though. We like at least having the stop words and tokenizer exceptions filled in by a native speaker, so the usual flow has been that someone needs the functionality, and they make a pull request.
If you just need the UD model for say, Bulgarian, you can do:
python -m spacy train xx /path/to/output_model /path/to/bulgarian-train.conllu /path/to/bulgarian-dev.conllu --no-entities