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Pérdida de tripletes y redes neuronales siamesas para entrenar la incrustación de artículos en catálogos

Comprender el contenido de un gran catálogo digital es un reto importante para las empresas en línea, pero este desafío puede abordarse utilizando modelos de redes neuronales autosupervisadas.

Using a Human-in-the-Loop to Overcome the Cold Start Problem in Menu Item Tagging

Companies with large digital catalogs often have lots of free text data about their items, but very few actual labels, making it difficult to analyze the data and develop new features. 

Building a system that can support machine learning (ML)-powered search and discovery features while simultaneously being interpretable enough for business users to develop curated experiences is difficult.