Video description
Dependency grammar is a powerful way to represent syntactic relationships within a sentence. More sophisticated than bag-of-words representations, it's used in natural language processing tasks like feature engineering, opinion mining, information retrieval, and relation extraction. In this course, which is designed for basic to intermediate level Python programmers, you'll learn how to represent dependency grammar as an extension to valency grammar and use it with spaCy.
- Discover valency grammar and how it's used to express word relationships
- Understand dependency grammar as a typed extension to valency grammar
- Explore the expressivity, assumptions, and limitations of dependency grammar
- Learn how to traverse parses with spaCy for various applications
- Gain experience training a spaCy parser on a Twitter dataset
Table of contents
-
Introduction
- Introduction 00:00:28
- About The Author 00:01:00
- Models Of Grammar 00:04:01
-
Dependency Grammar And Tagging
- Dependency Grammar 00:05:23
- Dependency Grammar With SpaCy Part - 1 00:04:22
- Dependency Grammar With SpaCy Part - 2 00:03:59
-
Training
- Training Your Own Parser 00:03:50
- Wrap Up 00:00:47
Product information
- Title: Dependency Grammar and Tagging with SpaCy
- Author(s):
- Release date: March 2017
- Publisher(s): Infinite Skills
- ISBN: 9781491982044
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