What is the importance of data augmentation in machine learning?

What is the importance of data augmentation in machine learning?

Data augmentation is crucial as it helps improve model performance by increasing the diversity of training data.

How does data augmentation help prevent overfitting?

By providing more varied examples, data augmentation helps the model generalize better, reducing the risk of overfitting.

Can you give me some common techniques used for data augmentation?

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

Is data augmentation only applicable to image data?

No, data augmentation can also be applied to text and audio data, using techniques like synonym replacement or pitch shifting.

What are the challenges associated with data augmentation?

Challenges include ensuring augmented data is realistic and relevant, and the computational cost of generating large datasets.