What is domain adaptation in AI?

What is domain adaptation in AI?

Domain adaptation is a technique in machine learning where a model trained on one domain is adapted to work effectively on another domain.

Can you give me an example of domain adaptation?

Sure! For instance, a model trained to recognize cats in photos from one dataset may need adaptation to recognize cats in a different dataset with different lighting or backgrounds.

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 techniques used for domain adaptation?

Common techniques include fine-tuning, feature alignment, and adversarial training to bridge the gap between domains.