Author: Akanksha NC

Effort to understand how particular classes could be more or less sensitive to the induction of noise in their labels, and to variations on the volume of training data used.

Effort to understand which is more hostile to accuracy: polluted information or reduced quantity.

Finding the right querying strategy for your models means understanding what your model learns quickly, what your model needs more of, and then reacting to that information. You can leverage that information to curate what you feed your models and what your organization collects and labels.

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