Democratizing NLP

Moshe Wasserblat on transfer learning, active learning, and other tools to help non-experts customize and fine-tune NLP models.

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Moshe Wasserblat is a Senior Principal Engineer at Intel, where he serves as a Research Manager focused on NLP and Deep Learning. Moshe and his team publish papers at leading academic conferences, but they also build tools for users within and beyond Intel. They’ve recently been building tools to help analysts and other non-expert NLP users, fine tune, test and customize NLP models for their specific domains and use cases.

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Moshe Wasserblat:

In a customer environment, you have a data science team that are experts in optimizing models. But when you go to production, you have business data analysts and other non-experts, and they are truly working with the system. You need to provide some simple tools for non-experts so that they can actually fine tune models. … Basically Active Learning for non-experts. This is quite powerful, because you get to empower the business owner to improve the system performance, and build the ontology for the domain.

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