A Visual Guide to Low-Resource NLP

Deep neural networks are becoming omnipresent in natural language applications (NLP). However, they require large amounts of labeled training data, which is often only available for English. This is a big challenge for many languages and domains where labeled data is limited. In recent years, a variety of methods have been proposed to tackle this situation. This article gives an overview of these approaches that help you train NLP models in resource-lean scenarios.