斯坦福NLP(自然语言处理)技术教程

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发表于 2021-7-17 11:10:16 | 显示全部楼层 |阅读模式
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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