Introduction to Natural Language Processing with SpaCy

SpaCy is a popular tool for beginners in natural language processing (NLP) that can be used for large-scale information extraction tasks. This course is designed for intermediate Python programmers and covers NLP challenges, as well as how spaCy can help solve them. The course teaches the basics of spaCy, including exploring the core data structure and model, visualizing and inferring key workflows, and learning about part-of-speech tags and their value. Additionally, students will learn the theory behind statistical part-of-speech tags and how to train a spaCy part-of-speech tagger using a new dataset. The course is taught by Aaron Kramer, a data scientist and engineer at DataScience Inc. in Los Angeles who is also a spaCy contributor and has authored several O'Reilly titles on NLP. This course is ideal for those seeking an introduction to NLP with Python, including natural language understanding and processing using spaCy.