Introduction to Natural Language Processing with SpaCy
Introduction to Natural Language Processing with SpaCy
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 29M | 110 MB
Genre: eLearning | Language: English
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
Introduction to Natural Language Processing with SpaCy
