When should I use data augmentation in machine learning?
An example of an AI chatbot conversation about when to apply data augmentation techniques.
When should I use data augmentation in machine learning?
Data augmentation is useful when you have a limited dataset and want to improve model generalization.
What are some common techniques for data augmentation?
Common techniques include rotation, flipping, scaling, and adding noise to images.
Can data augmentation help with overfitting?
Yes, it can help reduce overfitting by providing more diverse training examples.
Are there any downsides to using data augmentation?
One downside is that it can increase training time and may introduce noise if not done carefully.
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