斯坦福NLP（自然语言处理）技术教程
597012;注：纯英文课程，附英文字幕。【课程内容】
NLP Stanford
Week 1
Course IntroductionBasic Text ProcessingEdit Distance
Week 2
Language ModelingSpelling Correction
Week 3
Text_ClassificationSentiment_Analysis
Week 4
Discriminative classifiers- Maximum Entropy classifiersNamed entity recognition and Maximum Entropy Sequence ModelsRelation Extraction
Week 5
Advanced Maximum Entropy ModelsPOS TaggingParsing IntroductionInstructor Chat
Week 6
Probabilistic ParsingLexicalized ParsingDependency Parsing Optional
Week 7
Information RetrievalRanked Information Retrieval
Week 8
SemanticsQuestion AnsweringSummarizationInstructor Chat II
Natural Language Processing Collins
Week 1
Introduction to Natural Language ProcessingThe Language Modeling ProblemParameter Estimation in Language ModelsSummary
Week 2
Tagging Problems and Hidden Markov Models
Week 3
Parsing and Context-Free GrammarsProbabilistic Context-Free Grammars
Week 4
Weaknesses of PCFGsLexicalized PCFGs
Week 5
Introduction to Machine TranslationThe IBM Translation Models
Week 6
Phrase-based Translation ModelsDecoding of Phrase-based Translation Models
Week 7
Log-linear Models
Week 8
Log-linear Models for TaggingLog-Linear Models for History-based Parsing
Week 9
Unsupervised Learning- Brown ClusteringGlobal Linear Models
Week 10
GLMs for TaggingGLMs for Dependency Parsing
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