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Tart_Beginning t1_j3zutzn wrote

What is the difference between fine-tuning and transfer learning? Can you do deep learning without either of those things?

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trnka t1_j40i4fa wrote

Fine-tuning is when you take a pretrained network, change the output layer only, and run the optimizer a little more.

Transfer learning is when you take any sort of pretraining. Fine-tuning is one example of transfer learning. Using pretrained word embeddings is another example of transfer learning.

You can do deep learning without either. It's just that existing pretrained models and components are so good that it's tough to build a competitive model without either.

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