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Definition

Data Labeling

Data Labeling is the process of identifying raw data points (such as images, text, or audio files) and appending target category tags (labels) to them to create a labeled dataset for supervised learning.

Frequently Asked Questions

What is semi-supervised learning in relation to data labeling?

A training approach that combines a small amount of labeled data with a large amount of unlabeled data, allowing the model to propagate labels automatically to reduce labeling costs.

What are popular tools for automating data labeling?

Programmatic labeling tools like Snorkel, using weak supervision rules, or employing LLMs to draft initial label predictions for human review.

Quick Facts

  • CategoryModel Training
  • Key ApplicationSupervised training dataset preparation, human annotation setups, and labeling quality audits.

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