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Browse materialsMIT 6.864 · Fall 2005

Advanced Natural Language Processing

Subjects: Artificial Intelligence · Language · Science

Art: Palmer, Edward, 1803-1872, Figures 113-123. Plate Electrical Machines, 1840 · Public domain

Instructors: Prof. Michael Collins, Prof. Regina Barzilay
Term: Fall 2005
Level: Graduate
What's inside: 1 lecture note · 55 other files · 4 web pages
Materials open: MIT OCW

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About this course

Source: MIT OpenCourseWare 6.864 Advanced Natural Language Processing, Fall 2005, Prof. Michael Collins, Prof. Regina Barzilay — original course page on ocw.mit.edu ↗. License: CC BY-NC-SA 4.0. Study order: MIT's own listing order, section by section. Taken from MIT's published course files, downloaded from ocw.mit.edu on September 23, 2026. How RedLectern is built.

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Lecture Notes

25 files

Assignments

29 files

Other materials from this course

This resource is a supporting .gz file, contains data.txt file for the homework 3 (data.gz)GZIP archive Download

MIT OpenCourseWare, Prof. Michael Collins, Prof. Regina Barzilay, 6.864 Advanced Natural Language Processing, Fall 2005.

License: CC BY-NC-SA 4.0 · Edition: Fall 2005 · Open the original course on OCW ↗

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Advanced Natural Language Processing

Before you start

What's here, and what isn't

Not included here

Materials by section

Lecture Notes

Assignments

Other materials from this course

Lecture 1: Introduction and Overview

Lecture 2: Parsing and Syntax I

Lecture 3: Smoothed Estimation, and Language Modeling

Lecture 4: Parsing and Syntax II

Lecture 5: The EM Algorithm

Lecture 6: The EM Algorithm Part II

Lecture 7: Lexical Similarity

Lecture 8: Lexical Similarity (cont.)

Lecture 9: Log-Linear Models

Lecture 10: Tagging and History-based Models

Lecture 11: Grammar Induction

Lecture 12: Computational Modeling of Discourse

Lecture 13: Text Segmentation

Lecture 14: Local Coherence and Coreference

Lecture 15: Machine Translation

Lecture 16: Machine Translation (cont.)

Lecture 17: Machine Translation (cont.)

Lecture 18: Graph-based Methods for NLP Applications

Lecture 19: Word Sense Disambiguation

Lecture 20: Global Linear Models

Lecture 21: Global Linear Models Part II

Lecture 22: Dialogue Processing

Lecture 23: Dialogue Processing (cont.)

Lecture 24: Guest Lecture: Stephanie Seneff

Lecture 25: Text Summarization