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Artificial Intelligence & Machine Learning vocabulary · Data and Features

Data augmentation

Meaning in artificial intelligence & machine learning, with examples

nounCommon term

In artificial intelligence & machine learning, data augmentation means: Creating extra training examples by making small changes to existing ones, such as flipping or cropping images or rephrasing sentences, so that a model sees more variety.

In Turkish: veri artırma, veri çoğaltma

How it is used

Very common in computer vision and speech, and increasingly used in NLP. It helps reduce overfitting when data is limited. Engineers must check that a change keeps the label correct: a rotated '6' may turn into a '9'.

Example sentences

  1. Data augmentation with random crops and color changes added three points of accuracy.

  2. We turned off data augmentation for the validation set.

Common collocations

  • data augmentation techniques
  • apply data augmentation
  • image augmentation
  • augmentation pipeline
  • training dataThe examples a model learns from during training. Their quality, size and variety largely decide how well the model works on new data.
  • overfittingA problem in which a model learns its training data too closely, including noise and accidents, so it scores well on that data but poorly on new data.
  • preprocessingThe steps that clean and prepare raw data before a model uses it, such as removing duplicates, filling in missing values, resizing images or normalizing text.
  • computer visionThe area of AI that teaches computers to understand images and video, for example recognizing objects, reading text in photos or tracking movement.

This word in other fields

The same English word can have a different meaning in another field:

More terms: Data and Features

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