Few-Shot Learning

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Glossary

Few-Shot Learning

Few-Shot Learning to podejście w uczeniu maszynowym, które umożliwia modelom dokonywanie trafnych predykcji na podstawie jedynie niewielkiej liczby oznaczonych przykładów. W przeciwieństwie do tradycyjnych metod nadzorowanych, koncentruje się na uogólnianiu z ograniczonej ilości danych, wykorzystując techniki takie jak meta-learning, transfer learning oraz augmentację danych.

Few-Shot Learning Machine Learning Meta-Learning +2
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