Meta-Learning

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Glossary

Few-Shot Learning

Few-Shot Learning ist ein Ansatz im maschinellen Lernen, der es Modellen ermöglicht, genaue Vorhersagen mit nur einer kleinen Anzahl von gelabelten Beispielen zu treffen. Im Gegensatz zu traditionellen überwachten Methoden konzentriert er sich auf die Generalisierung aus begrenzten Daten und nutzt Techniken wie Meta-Lernen, Transferlernen und Datenaugmentation.

Few-Shot Learning Machine Learning Meta-Learning +2
• 6 min read

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