Home iMerit Briefing Note [CGBN157]

iMerit Briefing Note [CGBN157]

by rschmelzer

In order for many machine learning algorithms to be trained, especially supervised learning algorithms, they need to be fed relevant data that has been appropriately “labeled” with the required output that needs to be learned. However, there is a chicken-and-egg problem with systems automatically being able to label images (if they could automatically label the image, then why would you need to train them based on labeled images), all data labeling solutions are by their very nature human labor oriented. Humans must use their cognitive power to label and annotate images in such a way that machines can use those labels and annotations as part of the training process. iMerit provides “technology-enabled services” as they have tools to help humans provide the right annotations as well as verify and audit the annotations. They also recently partnered with with Amazon Web Services (AWS) to provide data labeling services on AWS SageMaker Ground Truth.


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iMerit-Briefing-Note-CGBN157.pdf
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  • May 10, 2019 Create Date
  • May 17, 2019 Last Updated

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