Detailed Information

Name LANGUAGE AND STATISTICS - CMU
Relevant to
Online URL LINK TO RESOURCE
Available at www.cs.cmu.edu
Suitable for Individual Study
Difficulty Level Intermediate
Type of Resource Notes
Social Recommendation
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What People Say

Excellent.
Reviewed by mark on 20 Feb 2017
Slightly advanced but has tons of information. You will definitely feel your mind expanding while completing this course :)
Reviewed by magic_logic on 10 Feb 2017
Top notch course in NLP. Jurafsky's is a bit better.
Reviewed by pauln on 27 Sep 2016

What Will I Learn

This course covers modern empirical methods in natural language processing. It is designed for language technologies students who want to more deeply understand statistical methodology in the language domain, and for machine learning students who want to know about current problems and solutions in text processing. Students will, upon completion, understand how statistical modeling and learning can be applied to linguistic analysis of text, be able to develop and apply new statistical models to problems in their own research, and be able to critically read papers from the major related conferences. A recurring theme will be the tradeoffs between computational cost, mathematical elegance, expressive power, and applicability to real problems. The course is organized around methods, with concrete examples introduced throughout.