What are some common data augmentation techniques used in machine learning?

What are some common data augmentation techniques used in machine learning?

Common data augmentation techniques include rotation, flipping, scaling, cropping, and color adjustment.

How does rotation help in data augmentation?

Rotation helps by providing the model with different perspectives of the same object, improving its robustness.

Can you explain how color adjustment works?

Color adjustment modifies the brightness, contrast, and saturation of images, helping the model generalize better.

Are there any specific techniques for text data augmentation?

Yes, techniques like synonym replacement, random insertion, and back-translation are commonly used for text data.