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For questions related to transfer learning, a machine learning method that focuses on storing knowledge gained while solving one problem in order to apply this knowledge to a different but related problem.

4 votes

What are the differences between transfer learning and meta learning?

The difference really comes down to the fact that in meta-learning, there is a population of tasks $\tau$ which have distribution $p(\tau)$. The goal is to perform well on a task drawn from $p(\tau)$. …
Chris Cundy's user avatar