What are some effective data augmentation techniques for machine learning?

What are some effective data augmentation techniques for machine learning?

Data augmentation techniques include rotation, flipping, scaling, and adding noise to images. Would you like to know more about a specific technique?

Can you explain how rotation works in data augmentation?

Sure! Rotation involves turning images at various angles to create new training samples, helping the model generalize better.

Are there any specific libraries I can use for data augmentation?

Yes! Libraries like TensorFlow, Keras, and Albumentations offer built-in functions for data augmentation.

How does data augmentation improve model performance?

It helps by increasing the diversity of the training dataset, reducing overfitting, and improving the model's ability to generalize.