Introduction to Natural Language Processing with SpaCy

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Introduction to Natural Language Processing with SpaCy

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 29M | 110 MB

Genre: eLearning | Language: English

 

SpaCy is an accessible tool that newcomers to the field of natural language processing (NLP) can use to accomplish large scale information extraction tasks.

In this course, which is designed for the intermediate level Python programmer, data scientist Aaron Kramer covers the challenges common to NLP, shows how the spaCy library for Python can address those challenges, explains how and why part-of-speech tagging is used in NLP, and provides you with the knowledge you need to extend spaCy for functional needs like sentiment models or relation extraction.

Learn the basics of using spaCy for common natural language processing tasks

Explore the core spaCy data structures and the data model

Learn how to see and intuit key workflows with spaCy

Understand part-of-speech tagging and its value

Learn the theory behind statistical part-of-speech tagging

Gain experience training a spaCy part-of-speech tagger on a new dataset

 

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