How do I choose the right transfer learning method?

What factors should I consider when choosing a transfer learning method?

You should consider the size of your dataset, the similarity between your source and target tasks, and the computational resources available.

Can you explain the difference between fine-tuning and feature extraction?

Sure! Fine-tuning involves training the entire model on your new dataset, while feature extraction uses the pre-trained model to extract features without modifying its weights.

When is it better to use fine-tuning over feature extraction?

Fine-tuning is better when you have a smaller dataset and need to adapt the model closely to your specific task.

Are there any specific models that are recommended for transfer learning?

Yes, popular models include VGG, ResNet, and BERT, depending on whether you're working with images or text.