How does transfer learning work?

Can you explain how transfer learning works in AI?

Sure! Transfer learning is a technique where a model developed for a specific task is reused as the starting point for a model on a second task.

Why is transfer learning useful?

It's useful because it allows us to leverage pre-trained models, saving time and resources, especially when data is scarce.

Can you give an example of transfer learning in action?

Absolutely! For instance, a model trained on a large dataset for image recognition can be fine-tuned for a specific task like identifying medical images.

What are the challenges of using transfer learning?

Some challenges include selecting the right pre-trained model and ensuring that the source and target tasks are sufficiently related.