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coursera-nlp

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种子名称： coursera-nlp
文件类型： 视频
文件数目： 121个文件
文件大小： 1.12 GB
收录时间： 2016-10-15 02:12
已经下载： 3次
资源热度： 84
最近下载： 2024-6-25 02:57

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coursera-nlp.torrent
  • lectures/week1-01/Natural Language Processing 0.0 Introduction (Part 1) (1117).mp414.18MB
  • lectures/week1-01/Natural Language Processing 0.1 Introduction (Part 2) (1028).mp411.86MB
  • lectures/week1-02/Natural Language Processing 1.0 Introduction to the Language Modeling Problem (Part 1) (617).mp47.49MB
  • lectures/week1-02/Natural Language Processing 1.1 Introduction to the Language Modeling Problem (Part 2) (712).mp48.33MB
  • lectures/week1-02/Natural Language Processing 1.2 Markov Processes (Part 1) (856).mp410.22MB
  • lectures/week1-02/Natural Language Processing 1.3 Markov Processes (Part 2) (628).mp47.35MB
  • lectures/week1-02/Natural Language Processing 1.4 Trigram Language Models (940).mp411.07MB
  • lectures/week1-02/Natural Language Processing 1.5 Evaluating Language Models Perplexity (1236).mp414.74MB
  • lectures/week1-03/Natural Language Processing 2.0 Linear Interpolation (Part 1) (746).mp49.07MB
  • lectures/week1-03/Natural Language Processing 2.1 Linear Interpolation (Part 2) (1135).mp413.67MB
  • lectures/week1-03/Natural Language Processing 2.2 Discounting Methods (Part 1) (926).mp411.19MB
  • lectures/week1-03/Natural Language Processing 2.3 Discounting Methods (Part 2) (334).mp44.43MB
  • lectures/week1-04/Natural Language Processing 3.0 Summary (231).mp43.01MB
  • lectures/week10-01/Natural Language Processing 18.0 Introduction (102).mp41.14MB
  • lectures/week10-01/Natural Language Processing 18.1 Recap of GLMs (740).mp49.18MB
  • lectures/week10-01/Natural Language Processing 18.2 GLMs for Tagging (Part 1) (526).mp46.94MB
  • lectures/week10-01/Natural Language Processing 18.3 GLMs for Tagging (Part 2) (735).mp49.32MB
  • lectures/week10-01/Natural Language Processing 18.4 GLMs for Tagging (Part 3) (706).mp48.71MB
  • lectures/week10-01/Natural Language Processing 18.5 GLMs for Tagging (Part 4) (600).mp47.23MB
  • lectures/week10-02/Natural Language Processing 19.0 Introduction (037).mp4699.68KB
  • lectures/week10-02/Natural Language Processing 19.1 The Dependency Parsing Problem (Part 1) (521).mp46.4MB
  • lectures/week10-02/Natural Language Processing 19.2 The Dependency Parsing Problem (Part 2) (1353).mp417.13MB
  • lectures/week10-02/Natural Language Processing 19.3 GLMs for Dependency Parsing (Part 1) (1159).mp414.15MB
  • lectures/week10-02/Natural Language Processing 19.4 GLMs for Dependency Parsing (Part 2) (828).mp410.98MB
  • lectures/week10-02/Natural Language Processing 19.5 Experiments with GLMs for Dep. Parsing (538).mp46.95MB
  • lectures/week10-02/Natural Language Processing 19.6 Summary (250).mp43.35MB
  • lectures/week2-01/Natural Language Processing 4.0 The Tagging Problem (1001).mp413.05MB
  • lectures/week2-01/Natural Language Processing 4.1 Generative Models for Supervised Learning (857).mp410.68MB
  • lectures/week2-01/Natural Language Processing 4.2 Hidden Markov Models (HMMs) Basic Definitions (1200).mp414.88MB
  • lectures/week2-01/Natural Language Processing 4.3 Parameter Estimation in HMMs (1316).mp416.27MB
  • lectures/week2-01/Natural Language Processing 4.4 The Viterbi Algorithm for HMMs (Part 1) (1407).mp417.01MB
  • lectures/week2-01/Natural Language Processing 4.5 The Viterbi Algorithm for HMMs (Part 2) (331).mp44.21MB
  • lectures/week2-01/Natural Language Processing 4.6 The Viterbi Algorithm for HMMs (Part 3) (733).mp49.27MB
  • lectures/week2-01/Natural Language Processing 4.7 Summary (150).mp42.22MB
  • lectures/week3-01/Natural Language Processing 5.0 Introduction (028).mp41016.68KB
  • lectures/week3-01/Natural Language Processing 5.1 Introduction to the Parsing Problem (Part 1) (1037).mp412.64MB
  • lectures/week3-01/Natural Language Processing 5.2 Introduction to the Parsing Problem (Part 2) (420).mp45.11MB
  • lectures/week3-01/Natural Language Processing 5.3 Context-Free Grammars (Part 1) (1211).mp414.52MB
  • lectures/week3-01/Natural Language Processing 5.4 Context-Free Grammars (Part 2) (222).mp42.79MB
  • lectures/week3-01/Natural Language Processing 5.5 A Simple Grammar for English (Part 1) (1032).mp412.57MB
  • lectures/week3-01/Natural Language Processing 5.6 A Simple Grammar for English (Part 2) (530).mp46.36MB
  • lectures/week3-01/Natural Language Processing 5.7 A Simple Grammar for English (Part 3) (1121).mp413.93MB
  • lectures/week3-01/Natural Language Processing 5.8 A Simple Grammar for English (Part 4) (220).mp42.85MB
  • lectures/week3-01/Natural Language Processing 5.9 Examples of Ambiguity (556).mp46.67MB
  • lectures/week3-02/Natural Language Processing 6.0 Introduction (112).mp41.29MB
  • lectures/week3-02/Natural Language Processing 6.1 Basics of PCFGs (Part 1) (943).mp411.61MB
  • lectures/week3-02/Natural Language Processing 6.2 Basics of PCFGs (Part 2) (826).mp410.82MB
  • lectures/week3-02/Natural Language Processing 6.3 The CKY Parsing Algorithm (Part 1) (731).mp49.35MB
  • lectures/week3-02/Natural Language Processing 6.4 The CKY Parsing Algorithm (Part 2) (1322).mp416.58MB
  • lectures/week3-02/Natural Language Processing 6.5 The CKY Parsing Algorithm (Part 3) (1007).mp412.38MB
  • lectures/week4-01/Natural Language Processing 7.0 Weaknesses of PCFGs (1459).mp417.93MB
  • lectures/week4-02/Natural Language Processing 8.0 Introduction (0017).mp4330.36KB
  • lectures/week4-02/Natural Language Processing 8.1 Lexicalization of a Treebank (1044).mp412.84MB
  • lectures/week4-02/Natural Language Processing 8.2 Lexicalized PCFGs Basic Definitions (1240).mp415.95MB
  • lectures/week4-02/Natural Language Processing 8.3 Parameter Estimation in Lexicalized PCFGs (Part 1) (528).mp46.53MB
  • lectures/week4-02/Natural Language Processing 8.4 Parameter Estimation in Lexicalized PCFGs (Part 2) (908).mp411.11MB
  • lectures/week4-02/Natural Language Processing 8.5 Evaluation of Lexicalized PCFGs (Part 1) (932).mp412.14MB
  • lectures/week4-02/Natural Language Processing 8.6 Evaluation of Lexicalized PCFGs (Part 2) (1128).mp414.31MB
  • lectures/week5-01/Natural Language Processing 9.0 Opening Comments (025).mp4452.36KB
  • lectures/week5-01/Natural Language Processing 9.1 introduction (203).mp42.36MB
  • lectures/week5-01/Natural Language Processing 9.2 Challenges in MT (806).mp49.37MB
  • lectures/week5-01/Natural Language Processing 9.3 Classical Approaches to MT (Part 1) (802).mp410MB
  • lectures/week5-01/Natural Language Processing 9.4 Classical Approaches to MT (Part 2) (556).mp47.27MB
  • lectures/week5-01/Natural Language Processing 9.5 Introduction to Statistical MT (1231).mp415.67MB
  • lectures/week5-02/Natural Language Processing 10.0 Introduction (324).mp43.96MB
  • lectures/week5-02/Natural Language Processing 10.1 IBM Model 1 (Part 1) (1306).mp416.08MB
  • lectures/week5-02/Natural Language Processing 10.2 IBM Model 1 (Part 2) (901).mp410.86MB
  • lectures/week5-02/Natural Language Processing 10.3 IBM Model 2 (1127).mp413.89MB
  • lectures/week5-02/Natural Language Processing 10.4 The EM Algorithm for IBM Model 2 (Part 1) (509).mp46.45MB
  • lectures/week5-02/Natural Language Processing 10.5 The EM Algorithm for IBM Model 2 (Part 2) (837).mp411.18MB
  • lectures/week5-02/Natural Language Processing 10.6 The EM Algorithm for IBM Model 2 (Part 3) (928).mp411.65MB
  • lectures/week5-02/Natural Language Processing 10.7 The EM Algorithm for IBM Model 2 (Part 4) (452).mp46.14MB
  • lectures/week5-02/Natural Language Processing 10.8 Summary (148).mp42.26MB
  • lectures/week6-01/Natural Language Processing 11.0 Introduction (041).mp4741.63KB
  • lectures/week6-01/Natural Language Processing 11.1 Learning Phrases from Alignments (Part 1) (918).mp411.54MB
  • lectures/week6-01/Natural Language Processing 11.2 Learning Phrases from Alignments (Part 2) (701).mp48.49MB
  • lectures/week6-01/Natural Language Processing 11.3 Learning Phrases from Alignments (Part 3) (847).mp411.11MB
  • lectures/week6-01/Natural Language Processing 11.4 A Sketch of Phrase-based Translation (817).mp49.86MB
  • lectures/week6-02/Natural Language Processing 12.0 Definition of the Decoding Problem (Part 1) (912).mp411.73MB
  • lectures/week6-02/Natural Language Processing 12.1 Definition of the Decoding Problem (Part 2) (1300).mp415.85MB
  • lectures/week6-02/Natural Language Processing 12.2 Definition of the Decoding Problem (Part 3) (1043).mp413.5MB
  • lectures/week6-02/Natural Language Processing 12.3 The Decoding Algorithm (Part 1) (1439).mp417.99MB
  • lectures/week6-02/Natural Language Processing 12.4 The Decoding Algorithm (Part 2) (623).mp47.59MB
  • lectures/week6-02/Natural Language Processing 12.5 The Decoding Algorithm (Part 3) (1229).mp415.93MB
  • lectures/week7-01/Natural Language Processing 13.0 Introduction (047).mp4849.63KB
  • lectures/week7-01/Natural Language Processing 13.1 Two Example Problems (1119).mp414.13MB
  • lectures/week7-01/Natural Language Processing 13.2 Features in Log-Linear Models (Part 1) (1356).mp417.13MB
  • lectures/week7-01/Natural Language Processing 13.3 Features in Log-Linear Models (Part 2) (1013).mp412.55MB
  • lectures/week7-01/Natural Language Processing 13.4 Definition of Log-linear Models (Part 1) (1150).mp414.61MB
  • lectures/week7-01/Natural Language Processing 13.5 Definition of Log-linear Models (Part 2) (345).mp44.53MB
  • lectures/week7-01/Natural Language Processing 13.6 Parameter Estimation in Log-linear Models (Part 1) (1244).mp415.55MB
  • lectures/week7-01/Natural Language Processing 13.7 Parameter Estimation in Log-linear Models (Part 2) (413).mp45.22MB
  • lectures/week7-01/Natural Language Processing 13.8 SmoothingRegularization in Log-linear Models (1512).mp419.25MB
  • lectures/week8-01/Natural Language Processing 14.0 Introduction (141).mp41.91MB
  • lectures/week8-01/Natural Language Processing 14.1 Recap of the Tagging Problem (315).mp44.31MB
  • lectures/week8-01/Natural Language Processing 14.2 Independence Assumptions in Log-linear Taggers (832).mp410.3MB
  • lectures/week8-01/Natural Language Processing 14.3 Features in Log-Linear Taggers (1321).mp416.32MB
  • lectures/week8-01/Natural Language Processing 14.4 Parameters in Log-linear Models (359).mp44.82MB
  • lectures/week8-01/Natural Language Processing 14.5 The Viterbi Algorithm for Log-linear Taggers (937).mp411.38MB
  • lectures/week8-01/Natural Language Processing 14.6 An Example Application (928).mp411.56MB
  • lectures/week8-01/Natural Language Processing 14.7 Summary (245).mp43.25MB
  • lectures/week8-02/Natural Language Processing 15.0 Introduction (047).mp4873.89KB
  • lectures/week8-02/Natural Language Processing 15.1 Conditional History-based Models (714).mp48.67MB
  • lectures/week8-02/Natural Language Processing 15.2 Representing Trees as Decision Sequences (Part 1) (723).mp48.72MB
  • lectures/week8-02/Natural Language Processing 15.3 Representing Trees as Decision Sequences (Part 2) (1020).mp411.98MB
  • lectures/week8-02/Natural Language Processing 15.4 Features and Beam Search (1210).mp414.65MB
  • lectures/week8-02/Natural Language Processing 15.5 Summary (112).mp41.38MB
  • lectures/week9-01/Natural Language Processing 16.0 Introduction (036).mp4670.94KB
  • lectures/week9-01/Natural Language Processing 16.1 Word Cluster Representations (836).mp411.06MB
  • lectures/week9-01/Natural Language Processing 16.2 The Brown Clustering Algorithm (Part 1) (1150).mp414.44MB
  • lectures/week9-01/Natural Language Processing 16.3 The Brown Clustering Algorithm (Part 2) (830).mp410.56MB
  • lectures/week9-01/Natural Language Processing 16.4 The Brown Clustering Algorithm (Part 3) (918).mp411.69MB
  • lectures/week9-01/Natural Language Processing 16.5 Clusters in NE Recognition (Part 1) (1133).mp415.31MB
  • lectures/week9-01/Natural Language Processing 16.6 Clusters in NE Recognition (Part 2) (728).mp48.88MB
  • lectures/week9-02/Natural Language Processing 17.0 Introduction (030).mp4574.81KB
  • lectures/week9-02/Natural Language Processing 17.1 Recap of History-based Models (711).mp49.01MB
  • lectures/week9-02/Natural Language Processing 17.2 Motivation for GLMs (634).mp47.86MB
  • lectures/week9-02/Natural Language Processing 17.3 Three Components of GLMs (1439).mp417.32MB
  • lectures/week9-02/Natural Language Processing 17.4 GLMs for Parse Reranking (1036).mp412.8MB
  • lectures/week9-02/Natural Language Processing 17.5 Parameter Estimation with the Perceptron Algorithm (611).mp47.32MB
  • lectures/week9-02/Natural Language Processing 17.6 Summary (301).mp43.76MB



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