Few-Shot Learning

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Glossary

Few-Shot Learning

Few-Shot Learning is een machine learning-benadering waarmee modellen nauwkeurige voorspellingen kunnen doen met slechts een klein aantal gelabelde voorbeelden. In tegenstelling tot traditionele supervisiemethoden richt het zich op generaliseren vanuit beperkte data, door gebruik te maken van technieken als meta-learning, transfer learning en data-augmentatie.

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