Dataturks – ML data annotations and labeling doesn't need to suck
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Re: Dataturks – ML data annotations and labeling doesn't need to suck
#2One of the things I'd look for in a product like this is easily doing rater reliability & interrater reliability.
Optimally I'd love to see a project also allow for easy semi-supervised labeling. I don't see an API for grabbing data points for a model you are training to label and put them back.
Re: Dataturks – ML data annotations and labeling doesn't need to suck
#3Do they keep copies?
That's important because in ML, data is everything.
Re: Dataturks – ML data annotations and labeling doesn't need to suck
#4> You and your team can now easily collaborate to build ML datasets super quick. Send email invite to anyone to help label your datasets, your team, friends, colleagues or external labelers. Pre-built support for more than a dozen data annotation use cases.
Re: Dataturks – ML data annotations and labeling doesn't need to suck
#5Re: Dataturks – ML data annotations and labeling doesn't need to suck
#6Do you guys know if there is any open-source project doing this kind of thing (UI for image labeling, NLP tagging, classification)? I think I've seen something like this before.
Re: Dataturks – ML data annotations and labeling doesn't need to suck
#7Re: Dataturks – ML data annotations and labeling doesn't need to suck
#8Do you guys know if there is any open-source project doing this kind of thing (UI for image labeling, NLP tagging, classification)? I think I've seen something like this before.
Re: Dataturks – ML data annotations and labeling doesn't need to suck
#9Re: Dataturks – ML data annotations and labeling doesn't need to suck
#10For work use, I'd need to host it on-prem. Otherwise even if it's great, legal etc won't let me use it.
Disclosure: I work at Labelbox.