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NLP Pipeline Basics with SpaCy

From tokenising words to Named Entity Recognition (NER) and everything in-between, SpaCy provides you all the NLP tools you might need for basic text processing to create features for training ML models on text data.

Demo Objectives

  • How to load a document and access sentences, tokens, and part-of-speech tags.
  • How to perform rules-based matching and phrase detection.
  • How to perform named entity recognition.

Running the Demo

This demo is contained within a single Jupyter notebook - demos/spacy/spacy_101.ipynb. Make sure you have the necessary Python package requirements installed into a Jupyter kernel for it to run successfully.