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Related Questions
- What is domain adaptation, and why is it important for pre-trained models?
- How does domain adaptation affect the performance of pre-trained models, and what are the common issues that arise?
- What are the key differences between domain adaptation and transfer learning, and how do they impact model adaptation?
- What are some common techniques used for domain adaptation, such as data augmentation, task adaptation, and multi-task learning?
- How does the choice of domain adaptation technique impact the model's performance, and what factors should be considered when selecting a technique?
- Can domain adaptation be used for unsupervised or semi-supervised learning, and what are the benefits and challenges of these approaches?
- What are some real-world applications of domain adaptation, such as adapting models for healthcare, finance, or education?
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