What are the benefits of data augmentation in machine learning?

What are the benefits of data augmentation in machine learning?

Data augmentation helps improve model performance by increasing the diversity of training data without collecting new data.

Can you give me some examples of data augmentation techniques?

Sure! Common techniques include rotation, flipping, scaling, and adding noise to images.

How does data augmentation help prevent overfitting?

By providing more varied data, it helps the model generalize better, reducing the risk of overfitting to the training set.

Is data augmentation only useful for image data?

No, it's also beneficial for text and audio data, enhancing the robustness of models across different domains.