Implement zero-shot learning on text to predict semantic relationships

Cerrado Publicado hace 5 años Pagado a la entrega
Cerrado Pagado a la entrega

I have triples such as:

(Justin - likes - apples)

(apples - color - red)

I would like to train such data using zero-shot learning to build a model to predict the relationship (second term in the triple). Zero-shot model known for the ability to predict objects that do not exist in the training set and that is what I want. For example, given the triple (man - .... - USA) the model should predict (lives) even if the relationship (lives) did not appear in the training data.

All the code should be using Python3.

inteligencia artificial Procesamiento de datos Machine Learning (ML) Python

Nº del proyecto: #18309196

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8 propuestas Proyecto remoto Activo hace 5 años

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schoudhary1553

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edecena75

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hamzaisb

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dinhfreedom

Dear sir. Your project attracted my attention at first glance, because I've extensive experience in Predicting Semantic Relations Programming. I'm really confident about your project, and very eager to join your proj Más

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liveexperts123

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