Text Processing Course: Introduction to Natural Language Processing

Name: Introduction to Natural Language Processing

Website:

Description

This course provides an introduction to the field of Natural Language Processing, including topics like Language Models, Parsing, Semantics, Question Answering, and Sentiment Analysis.

This course provides an introduction to the field of Natural Language Processing. It includes relevant background material in Linguistics, Mathematics, Probabilities, and Computer Science. Some of the topics covered in the class are Text Similarity, Part of Speech Tagging, Parsing, Semantics, Question Answering, Sentiment Analysis, and Text Summarization.
The course includes quizzes, programming assignments in python, and a final exam.

Course Syllabus
Week One (Introduction 1/2) (1:35:31)
Week Two (Introduction 2/2) (1:36:26)
Week Three (NLP Tasks and Text Similarity) (1:42:52)
Week Four (Syntax and Parsing, Part 1) (1:48:14)
Week Five (Syntax and Parsing, Part 2) (1:50:29)
Week Six (Language Modeling and Word Sense Disambiguation) (1:40:33)
Week Seven (Part of Speech Tagging and Information Extraction) (1:33:21)
Week Eight (Question Answering) (1:16:59)
Week Nine (Text Summarization) (1:33:55)
Week Ten (Collocations and Information Retrieval) (1:29:40)
Week Eleven (Sentiment Analysis and Semantics) (1:09:38)
Week Twelve (Discourse, Machine Translation, and Generation) (1:30:57)

About the Instructors

Dragomir R. Radev, Ph.D.
Professor of Information, School of Information, Professor of Electrical Engineering and Computer Science, College of Engineering, and Professor of Linguistics, College of Literature, Science, and the Arts
University of Michigan
Among his many accomplishments, Dragomir Radev was cited for being an
international leader in computational linguistics, and contributing
significantly to automatic methods to extract content from text,
including data mining, Web graph and network analysis, and
bioinformatics. Using natural language processing, information
retrieval, and machine learning, he makes sense of the exploding
volume of digital content.

Professor Radev was the first to develop ways to generate informative
summaries from multiple online sources, addressing for the first time
this important problem. Before joining the University of Michigan
faculty in 2000, he worked at IBM’s T.J. Watson Research Center. At
IBM, he co-authored three patents, one of which was for a forerunner to
the Watson Q&A Engine.

Professor Radev is one of the co-founders of the North American
Computational Linguistics Olympiad (NACLO), which began in 2006. This
event for high school and middle school students from the U.S. and
Canada introduces the field of computational linguistics through
competitions to solve linguistic puzzles using analytic
reasoning. Each year, he has coached and traveled with the
U.S. national teams who participate in the International Linguistics
Olympiad and has returned with several gold medals. In 2011, Radev and
his fellow organizers received the Linguistics, Language and the
Public Award from the Linguistic Society of America.

Radev is Professor of Information (in the School of Information),
Professor of Electrical Engineering and Computer Science (in the
College of Engineering) and Professor of Linguistics (in the College
of Literature, Science and the Arts).

Dragomir Radev is an ACM Distinguished Scientist and the recipient of
the University of Michigan Faculty Recognition Award and Outstanding
Mentorship Award.


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