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What is the difference between one-shot learning, transfer learning and fine tuning?

They are all related terms. From top to bottom: One-shot learning aims to achieve results with one or very few examples. Imagine an image classification task. You may show an apple and a knife to a ...
Pablo's user avatar
  • 226
1 vote

Precise description of one-shot learning

The model has learnt the "features" for the type of inputs, eg. faces. For the problem to be called one-shot, it needs to also correctly classify/compare any new samples. For example, in face ...
SajanGohil's user avatar

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