ML-Assisted Data Annotation

As AI applications increase in number and scope, the need for mass amounts of high-quality training data is rising. This poses a number of challenges, from scalability to flexibility to speed. Collaboration between humans and machines is the solution. By integrating machine learning models and automation tools into the annotation process — and balancing them with the context and judgment that human annotators bring to the table — companies can achieve outstanding results.

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