Zero-Shot Learning in Modern NLP

Natural language processing is a very exciting field right now. In recent years, the community has begun to figure out some pretty effective methods of learning from the enormous amounts of unlabeled data available on the internet.

Traditionally, zero-shot learning (ZSL) most often referred to a fairly specific type of task: learn a classifier on one set of labels and then evaluate on a different set of labels that the classifier has never seen before. Recently, especially in NLP, it’s been used much more broadly to mean get a model to do something that it wasn’t explicitly trained to do. In this session, we will explore how to run unsupervised text sentiment analysis with popular NLP library Hugging Face. We will look into ways how this innovative NLP approach can be integrated with Oracle tech.