Sofie’s Blog
A diagram showing how a spaCy pipeline consists of several components running in sequence: e.g. first a tagger, then a parser, then NER.

Building customizable NLP pipelines with spaCy

spaCy is an industrial-strength Natural Language Processing library which allows you to quickly build performant pipelines to tackle specific NLP challenges. It comes with pretrained Machine Learning models for 10 languages and has basic support for over 50 languages. In this talk, I showcase the usage of spaCy as well as give a peak preview on the upcoming spaCy v.3 which will give the user full control over the model internals via configuration files.

→  Venue: Turku.AI Meetup (Turku, Finland)

→  Slides: Speakerdeck