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Labeling methods are becoming increasingly important to the success of Machine Learning.

With up to half the time on an AI project spent dealing with data, the success or failure of these endeavors rely on labeling methods. A recent survey revealed that 79% of respondents with data labeling experience use the in-house approach even while being aware of certain drawbacks of this method. Are there better data labeling approaches and tools to use in ML solutions today?

We would like to check a few things with you via a very simple survey.
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Which data labeling solutions have you ever heard of? *
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Which data labeling solution(s) is used in your organisation? *
Which data labeling solution(s) are you using for your personal projects? *
To learn more about solutions for your data labeling issues (if any), you would prefer to: *
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