Chapter 1: Finding words, phrases, names and concepts

This chapter will introduce you to the basics of text processing with spaCy. You'll learn about the data structures, how to work with trained pipelines, and how to use them to predict linguistic features in your text.

1Introduction to spaCy

2Getting Started

3Documents, spans and tokens

4Lexical attributes

5Trained pipelines

6Pipeline packages

7Loading pipelines

8Predicting linguistic annotations

9Predicting named entities in context

10Rule-based matching

11Using the Matcher

12Writing match patterns

About this course

spaCy is a modern Python library for industrial-strength Natural Language Processing. In this free and interactive online course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

About me

I'm Ines, one of the core developers of spaCy and the co-founder of Explosion. I specialize in modern developer tools for AI, Machine Learning and NLP. I also really love building stuff for the web.