NAVIGATION
Definition

Data Augmentation

Data Augmentation is the practice of artificially increasing the size and diversity of a training dataset by applying transformations (like cropping, rotating, flipping, or paraphrasing) to existing data points.

Frequently Asked Questions

How does data augmentation prevent overfitting?

By presenting slightly different variations of the inputs, it prevents the model from memorizing specific training pixels or tokens.

Can you use LLMs for data augmentation?

Yes, LLMs are frequently used to generate paraphrased variants of sentences to expand text training datasets.

Quick Facts

  • CategoryModel Training
  • Key ApplicationImage model training, synthetic text expansion, and overfitting prevention

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