What is data augmentation and how is it used in various fields?

What is data augmentation and how is it used in various fields?

Data augmentation is a technique used to increase the diversity of your training dataset by applying various transformations. It's widely used in fields like computer vision, natural language processing, and audio processing.

Can you give me some examples of data augmentation techniques?

Sure! In image processing, techniques include rotation, flipping, and color adjustment. For text, you might use synonym replacement or back-translation.

How does data augmentation improve model performance?

It helps prevent overfitting by providing more varied data, allowing models to generalize better to unseen data.

Are there any specific domains where data augmentation is particularly beneficial?

Yes, in medical imaging, data augmentation can help create more robust models despite limited data availability.