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Related Questions
- What are the key differences between few-shot learning and traditional machine learning approaches?
- How does meta-learning relate to few-shot learning, and what are its benefits?
- Can you explain the concept of episodic training and its role in few-shot learning?
- How does few-shot learning prevent overfitting, and what are the implications for model generalizability?
- Can you provide examples of applications where few-shot learning has been successfully used to prevent overfitting?
- What are the challenges and limitations of few-shot learning, and how can they be addressed?
- How does few-shot learning compare to transfer learning in terms of preventing overfitting, and what are the trade-offs?
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