What are the main challenges of transfer learning in AI?

What are the main challenges of transfer learning in AI?

Transfer learning can face several challenges, including domain shift, data scarcity, and overfitting.

Can you explain what domain shift means?

Domain shift refers to the differences between the source domain (where the model is trained) and the target domain (where it's applied), which can hinder performance.

How can we mitigate the effects of overfitting in transfer learning?

To mitigate overfitting, techniques like regularization, dropout, and using a smaller learning rate can be effective.

Are there specific applications where transfer learning is particularly useful?

Yes, transfer learning is especially useful in areas like image recognition, natural language processing, and medical diagnosis.