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Related Questions
- Can data augmentation techniques such as data augmentation by rotation or flipping be used to prevent overfitting in deep learning models?
- How can synthetic data generated through data augmentation be used to increase the size and diversity of training datasets?
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- Can data augmentation be used to improve the robustness of machine learning models to adversarial attacks?
- How can data augmentation be used to balance the class distribution in imbalanced datasets?
- What are the potential risks of over-augmentation, and how can they be mitigated?
- Can data augmentation be used to transfer knowledge from one domain to another in multi-task learning?
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