What is domain adaptation?
An example of an AI chatbot conversation about domain adaptation in machine learning.
What is domain adaptation?
Domain adaptation is a technique in machine learning where a model trained on one domain is adapted to work on another domain.
Can you give me an example of domain adaptation?
Sure! For instance, a model trained to recognize cats in photos taken in bright daylight may need adaptation to recognize cats in low-light conditions.
Why is domain adaptation important?
It's important because it helps improve the model's performance in real-world scenarios where data may differ from the training set.
What are some common methods used for domain adaptation?
Common methods include fine-tuning, adversarial training, and using domain-invariant features.
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