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Natural Language Processing
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Natural Language Processing
Dan Jurafsky,
Professor of Linguistics
Chris Manning,
Associate Professor of Computer Science
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Video Lectures
Week 1 - Course Introduction
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Completed
Course Introduction (14:11)
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Week 1 - Basic Text Processing
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Completed
Regular Expressions (11:25)
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Completed
Regular Expressions in Practical NLP (6:04)
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Completed
Word Tokenization (14:26)
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Completed
Word Normalization and Stemming (11:47)
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Completed
Sentence Segmentation (5:31)
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Week 1 - Edit Distance
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Completed
Defining Minimum Edit Distance (7:04)
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Completed
Computing Minimum Edit Distance (5:54)
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Completed
Backtrace for Computing Alignments (5:55)
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Completed
Weighted Minimum Edit Distance (2:47)
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Completed
Minimum Edit Distance in Computational Biology (9:29)
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Week 2 - Language Modeling
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Completed
Introduction to N-grams (8:41)
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Completed
Estimating N-gram Probabilities (9:38)
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Completed
Evaluation and Perplexity (11:09)
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Completed
Generalization and Zeros (5:15)
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Completed
Smoothing: Add-One (6:30)
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Completed
Interpolation (10:25)
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Completed
Good-Turing Smoothing (15:35)
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Completed
Kneser-Ney Smoothing (8:59)
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Week 2 - Spelling Correction
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Completed
The Spelling Correction Task (5:39)
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Completed
The Noisy Channel Model of Spelling (19:30)
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Completed
Real-Word Spelling Correction (9:19)
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Completed
State of the Art Systems (7:10)
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Week 3 - Text Classification
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Completed
What is Text Classification? (8:12)
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Completed
Naive Bayes (3:19)
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Completed
Formalizing the Naive Bayes Classifier (9:28)
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Completed
Naive Bayes: Learning (5:22)
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Completed
Naive Bayes: Relationship to Language Modeling (4:35)
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Completed
Multinomial Naive Bayes: A Worked Example (8:58)
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Completed
Precision, Recall, and the F measure (16:16)
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Completed
Text Classification: Evaluation (7:17)
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Completed
Practical Issues in Text Classification (5:56)
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Week 3 - Sentiment Analysis
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Completed
What is Sentiment Analysis? (7:17)
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Completed
Sentiment Analysis: A baseline algorithm (13:27)
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Completed
Sentiment Lexicons (8:37)
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Completed
Learning Sentiment Lexicons (14:45)
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Completed
Other Sentiment Tasks (11:01)
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Week 4 - Discriminative classifiers: Maximum Entropy classifiers
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Completed
Generative vs. Discriminative Models (7:49)
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Completed
Making features from text for discriminative NLP models (18:11)
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Completed
Feature-Based Linear Classifiers (13:34)
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Completed
Building a Maxent Model: The Nuts and Bolts (8:04)
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Completed
Generative vs. Discriminative models: The problem of overcounting evidence (12:15)
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Completed
Maximizing the Likelihood (10:29)
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Week 4 - Named entity recognition and Maximum Entropy Sequence Models
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Completed
Introduction to Information Extraction (9:18)
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Completed
Evaluation of Named Entity Recognition (6:34)
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Completed
Sequence Models for Named Entity Recognition (15:05)
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Completed
Maximum Entropy Sequence Models (13:01)
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Week 4 - Relation Extraction
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Completed
What is Relation Extraction? (9:47)
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Completed
Using Patterns to Extract Relations (6:17)
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Completed
Supervised Relation Extraction (10:51)
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Completed
Semi-Supervised and Unsupervised Relation Extraction (9:53)
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Week 5 - Advanced Maximum Entropy Models
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Completed
The Maximum Entropy Model Presentation (12:14)
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Completed
Feature Overlap/Feature Interaction (12:51)
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Completed
Conditional Maxent Models for Classification (4:11)
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Completed
Smoothing/Regularization/Priors for Maxent Models (29:24)
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Week 5 - POS Tagging
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Completed
An Intro to Parts of Speech and POS Tagging (13:19)
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Completed
Some Methods and Results on Sequence Models for POS Tagging (13:04)
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Week 5 - Parsing Introduction
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Completed
Syntactic Structure: Constituency vs Dependency (8:46)
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Completed
Empirical/Data-Driven Approach to Parsing (7:11)
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Completed
The Exponential Problem in Parsing (14:30)
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Week 5 - Instructor Chat
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Completed
Instructor Chat (9:02)
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Week 6 - Probabilistic Parsing
(collapsed, click to expand)
Completed
CFGs and PCFGs (15:29)
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Completed
Grammar Transforms (12:05)
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Completed
CKY Parsing (23:25)
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Completed
CKY Example (21:52)
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Completed
Constituency Parser Evaluation (9:45)
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Week 6 - Lexicalized Parsing
(collapsed, click to expand)
Completed
Lexicalization of PCFGs (7:03)
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Completed
Charniak's Model (18:23)
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Completed
PCFG Independence Assumptions (9:44)
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Completed
The Return of Unlexicalized PCFGs (20:53)
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Completed
Latent Variable PCFGs (12:07)
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Week 6 - Dependency Parsing (Optional)
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Completed
Dependency Parsing Introduction (10:25)
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Completed
Greedy Transition-Based Parsing (31:05)
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Completed
Dependencies Encode Relational Structure (7:20)
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Week 7 - Information Retrieval
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Introduction to Information Retrieval (9:16)
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Completed
Term-Document Incidence Matrices (8:59)
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Completed
The Inverted Index (10:42)
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Completed
Query Processing with the Inverted Index (6:43)
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Completed
Phrase Queries and Positional Indexes (19:45)
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Week 7 - Ranked Information Retrieval
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Introducing Ranked Retrieval (4:27)
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Completed
Scoring with the Jaccard Coefficient (5:06)
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Completed
Term Frequency Weighting (5:59)
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Completed
Inverse Document Frequency Weighting (10:16)
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Completed
TF-IDF Weighting (3:42)
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Completed
The Vector Space Model (16:22)
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Completed
Calculating TF-IDF Cosine Scores (12:47)
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Completed
Evaluating Search Engines (9:02)
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Week 8 - Semantics
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Completed
Word Senses and Word Relations (11:50)
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Completed
WordNet and Other Online Thesauri (6:23)
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Completed
Word Similarity and Thesaurus Methods (16:17)
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Completed
Word Similarity: Distributional Similarity I (13:14)
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Completed
Word Similarity: Distributional Similarity II (8:15)
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Week 8 - Question Answering
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Completed
What is Question Answering? (7:28)
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Completed
Answer Types and Query Formulation (8:47)
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Completed
Passage Retrieval and Answer Extraction (6:38)
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Completed
Using Knowledge in QA (4:25)
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Completed
Advanced: Answering Complex Questions (4:52)
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Week 8 - Summarization
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Completed
Introduction to Summarization
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Completed
Generating Snippets
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Completed
Evaluating Summaries: ROUGE
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Completed
Summarizing Multiple Documents
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Week 8 - Instructor Chat II
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Completed
Instructor Chat II (5:23)
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