What is the difference between transfer learning and traditional learning?

What is the difference between transfer learning and traditional learning?

Transfer learning involves using a pre-trained model on a new task, while traditional learning trains a model from scratch.

Can you give me an example of transfer learning in action?

Sure! A common example is using a model trained on ImageNet to classify medical images.

What are the advantages of using transfer learning?

Transfer learning can save time and resources, improve performance on small datasets, and leverage existing knowledge.

Are there any downsides to transfer learning?

Yes, transfer learning can lead to negative transfer if the source and target tasks are too different.