@ivan_uvarov many thanks! Handl crowd is good for general tasks. You can assign tasks to groups of workers each of which is focused on a specific area. But if labeling requires the knowledge of Chinese or medical education, you may need your in-house team.
@batyr not really, Handl stands for machine learning data annotation. Mechanical Turk or similar would better fit jobs related to content management.
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Looks really really interesting! Questions:
1) What is the maximum and the minimum data volume for labeling?
2) Can we buy ready "cats" (for example) vertical datasets? Is it going to be a marketplace for different verticals?
3) What other datasets verticals do you have?
@goldenalf13 thanks Andrew! We can deal with any data volume and we have a flexile pricing for that. For now, we work with client's data only. We do not trade in any way.
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Excellent Job. The keyboard shortcuts are (IMHO) a critical feature and I'm glad that it "just worked" as expected. I can see this being quite valuable in security-sensitive domains such as government or big enterprise. Is that where you see this going?
Regardless, great job!
@jake_quist Many thanks, this is also a favourite feature of our labelers! For clients with sensitive data, we provide an opportunity to work with our interfaces using their in-house team.
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Any plans to open source any of it or make it embeddable into existing workflows? Would also love to learn more about any future plans pertaining to audio labeling
Pros:
Seems like a great tool for image annotation, 25k users on board is an impressive metric, and the product is very straightforward
Cons:
Curious about the difference between Handl, Alegion, and Clickworker's image annotation
Norm Model B Desk
OneSoil
Norm Model B Desk
TripleTen
Norm Model B Desk
Norm Model B Desk
Norm Model B Desk
TripleTen
Any plans to open source any of it or make it embeddable into existing workflows? Would also love to learn more about any future plans pertaining to audio labeling
Pros:Seems like a great tool for image annotation, 25k users on board is an impressive metric, and the product is very straightforward
Cons:Curious about the difference between Handl, Alegion, and Clickworker's image annotation