Course Features
Duration
5 hours
Delivery Method
Online
Available on
Limited Access
Accessibility
Mobile, Desktop, Laptop
Language
English
Subtitles
English
Level
Advanced
Teaching Type
Self Paced
Video Content
5 hours
Course Description
Course Overview
Virtual Labs
International Faculty
Post Course Interactions
Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
Introduction to Natural Language Processing in Python
What You Will Learn
Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches
In this course, you'll learn how to use spaCy, a fast-growing industry standard library for NLP in Python, to build advanced natural language understanding systems, using both rule-based and machine learning approaches
Course Content
Module 1: Finding words, phrases, names and concepts
1. Introduction to spaCy
2. Getting Started
3. Documents, spans and tokens
4. Lexical attributes
5. Statistical models
6. Model packages
7. Loading models
8. Predicting linguistic annotations
9. Predicting named entities in context
10. Rule-based matching
11. Using the Matcher
12. Writing match patterns
Course Instructors
Course Reviews
Average Rating Based on 3 reviews
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