Meta-Learning

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Glossary

Aprendizaje de Pocos Ejemplos (Few-Shot Learning)

El aprendizaje de pocos ejemplos es un enfoque de aprendizaje automático que permite a los modelos hacer predicciones precisas utilizando solo un pequeño número de ejemplos etiquetados. A diferencia de los métodos supervisados tradicionales, se enfoca en generalizar a partir de datos limitados, aprovechando técnicas como meta-aprendizaje, aprendizaje por transferencia y aumento de datos.

Few-Shot Learning Machine Learning Meta-Learning +2
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