Instruction: Discuss whether and how transfer learning affects the use of data augmentation techniques in the training process.
Context: Candidates should address the interplay between the richness of pre-trained models and the need for expanding or adjusting the target dataset, showcasing their practical knowledge of data handling.
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The way I'd approach it in an interview is this: Transfer learning often reduces how much augmentation you need because the pretrained model already brings useful invariances and representations. But it does not eliminate augmentation entirely, especially when the...