Chapter 2: Large-scale data analysis with spaCy

In this chapter, you'll use your new skills to extract specific information from large volumes of text. You'll learn how to make the most of spaCy's data structures, and how to effectively combine statistical and rule-based approaches for text analysis.

1Data Structures (1)

2Strings to hashes

3Vocab, hashes and lexemes

4Data Structures (2)

5Creating a Doc

6Docs, spans and entities from scratch

7Data structures best practices

8Word vectors and semantic similarity

9Inspecting word vectors

10Comparing similarities

11Combining predictions and rules

12Debugging patterns (1)

13Debugging patterns (2)

14Efficient phrase matching

15Extracting countries and relationships

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.