CS224N  Natural Language Processing
CS224N: Natural Language Processing (Stanford Univ.). Instructor: Professor Christopher D. Manning. This course is designed to introduce students to the fundamental concepts
and ideas in natural language processing (NLP), and to get them up to speed with current research in the area. It develops an indepth understanding of both the algorithms available for
the processing of linguistic information and the underlying computational properties of natural languages. Wordlevel, syntactic, and semantic processing from both a linguistic and
an algorithmic perspective are considered. The focus is on modern quantitative techniques in NLP: using large corpora, statistical models for acquisition, disambiguation, and parsing.
Also, it examines and constructs representative systems. (from see.stanford.edu)
Lecture 01  Course Introduction, Why NLP Is Difficult?, Machine Translation 
Lecture 02  Questions That Linguistics Should Answer, Probabilistic Language Models, Smoothing 
Lecture 03  Smoothing, KneserNey Smoothing, Practical Considerations 
Lecture 04  Review Statistical MT, Model 1, The Em Algorithm 
Lecture 05  IBM Models, MT Evaluation, Bleu Evaluation Metric 
Lecture 06  SyntaxBased Model, Information Extraction & Named Entity Recognition 
Lecture 07  Naive Bayes Classifier, Joint vs. Conditional Models, FeatureBased Classifiers 
Lecture 08  Details of Maxent Model, Maxent Examples 
Lecture 09  MEMM (Maximum Entropy Markov Model), HMM Pos Tagging Models 
Lecture 10  Statistical Natural Language Parsing 
Lecture 11  Polynomial Time Parsing of PCFGs (Probabilistic ContextFree Grammars) 
Lecture 12  Semantic Role Labeling 
Lecture 13  Lexicalized Parsing 
Lecture 14  Parsing as Search, AgendaBased Parsing, Dependency Parsing 
Lecture 15  Why Study Computational Semantics? 
Lecture 16  An Introduction to Formal Computational Semantics 
Lecture 17  Lexical Semantics, Lexical Information and NL Applications 
Lecture 18  Question Answering Systems and Textual Inference 
References 
CS224N  Natural Language Processing
Instructors: Professor Christopher D. Manning. Handouts. Assignments. Exams. This course is designed to introduce students to the fundamental concepts and ideas in natural language processing (NLP).
