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Related Questions
- What are some common data augmentation techniques used in deep learning, and how can they be applied to improve model performance?
- How can transfer learning be combined with data augmentation to leverage pre-trained models and improve generalizability?
- What are some best practices for selecting the right data augmentation techniques and transfer learning approaches for a specific problem?
- Can you provide examples of how data augmentation can be used to augment datasets for image classification, object detection, and natural language processing tasks?
- How can data augmentation and transfer learning be used together to improve robustness and adaptability of models to new, unseen data?
- What are some challenges and limitations of using data augmentation and transfer learning together, and how can they be addressed?
- Can you discuss the role of data augmentation in reducing overfitting and improving model generalizability when combined with transfer learning?
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