O'Reilly - Dependency Grammar and Tagging with SpaCy

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O'Reilly - Dependency Grammar and Tagging with SpaCy
Duration: 25m | Video: h264, 1280x720 | Audio: AAC, 44100 Hz, 2 Ch | 73 MB
Genre: eLearning | Language: English | Project Files

by Aaron Kramer
Publisher: Infinite Skills
Release Date: March 2017
ISBN: 9781491982051
Topics: Python

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 00:00:28
About The Author 00:01:00
Models Of Grammar 00:04:01
How To Access Your Working Files 00:01:15
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 Your Own Parser 00:03:50
Wrap Up 00:00:47

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Tags: Reilly, Dependency, Grammar, Tagging
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