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Related Questions
- Can you explain the concept of domain adaptation and its importance in transfer learning?
- What are the key challenges in adapting a pre-trained model to a new task, and how does domain adaptation address these challenges?
- How does domain adaptation enable a model to generalize better to a new task, and what are the benefits of this approach?
- What are some common techniques used in domain adaptation, and how do they differ from each other?
- Can you discuss the relationship between domain adaptation and few-shot learning, and how they can be combined?
- What are some common applications of domain adaptation in real-world scenarios, such as natural language processing and computer vision?
- How does domain adaptation handle the issue of distribution shift, and what are the implications for model performance?
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