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Natural Language Processing

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Natural Language Processing

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Total Size

1.4 GB

Total Files

505

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111E8DAD4AEC6FCCEFF2FB5C29DB95CD8F1F3D53

/17 - Week 6 - Dependency Parsing (Optional)/

17 - 2 - Greedy Transition-Based Parsing (31_05).mp4

32.9 MB

17 - 1 - Dependency Parsing Introduction (10_25).mp4

11.7 MB

17 - 3 - Dependencies Encode Relational Structure (7_20).mp4

7.6 MB

slides_Parsing-16-Stanford-Dependencies.pptx

834.4 KB

slides_Parsing-14-Dependency-Intro.pptx

813.0 KB

slides_Parsing-15-Dependency-Transition-Based.pptx

784.4 KB

slides_Parsing-16-Stanford-Dependencies.pdf

745.3 KB

slides_Parsing-15-Dependency-Transition-Based.pdf

704.0 KB

slides_Parsing-14-Dependency-Intro.pdf

685.9 KB

17 - 2 - Greedy Transition-Based Parsing (31_05).srt

38.4 KB

17 - 2 - Greedy Transition-Based Parsing (31_05).txt

26.2 KB

17 - 1 - Dependency Parsing Introduction (10_25).srt

13.1 KB

17 - 3 - Dependencies Encode Relational Structure (7_20).srt

9.3 KB

17 - 1 - Dependency Parsing Introduction (10_25).txt

9.0 KB

17 - 3 - Dependencies Encode Relational Structure (7_20).txt

6.1 KB

/11 - Week 5 - Advanced Maximum Entropy Models/

11 - 4 - Smoothing_Regularization_Priors for Maxent Models (29_24).mp4

30.2 MB

11 - 1 - The Maximum Entropy Model Presentation (12_14).mp4

18.1 MB

11 - 2 - Feature Overlap_Feature Interaction (12_51).mp4

13.2 MB

11 - 3 - Conditional Maxent Models for Classification (4_11).mp4

5.0 MB

slides_05-04-Maxent_Smoothing.pptx

1.3 MB

slides_05-04-Maxent_Smoothing.pdf

1.2 MB

slides_05-01-Maxent_Model_Formulation.pptx

1.2 MB

slides_05-01-Maxent_Model_Formulation.pdf

1.1 MB

slides_05-03-Maxent_Classification.pptx

769.7 KB

slides_05-03-Maxent_Classification.pdf

760.1 KB

slides_05-02-Maxent_Feature_Overlap.pptx

659.2 KB

slides_05-02-Maxent_Feature_Overlap.pdf

627.3 KB

11 - 4 - Smoothing_Regularization_Priors for Maxent Models (29_24).srt

37.5 KB

11 - 4 - Smoothing_Regularization_Priors for Maxent Models (29_24).txt

25.6 KB

11 - 2 - Feature Overlap_Feature Interaction (12_51).srt

16.6 KB

11 - 1 - The Maximum Entropy Model Presentation (12_14).srt

15.4 KB

11 - 2 - Feature Overlap_Feature Interaction (12_51).txt

11.4 KB

11 - 1 - The Maximum Entropy Model Presentation (12_14).txt

10.5 KB

11 - 3 - Conditional Maxent Models for Classification (4_11).srt

5.1 KB

11 - 3 - Conditional Maxent Models for Classification (4_11).txt

3.5 KB

/15 - Week 6 - Probabilistic Parsing/

15 - 3 - CKY Parsing (23_25).mp4

27.5 MB

15 - 4 - CKY Example (21_52).mp4

24.6 MB

15 - 1 - CFGs and PCFGs (15_29).mp4

17.5 MB

15 - 2 - Grammar Transforms (12_05).mp4

12.6 MB

15 - 5 - Constituency Parser Evaluation (9_45).mp4

11.2 MB

slides_Parsing-04-CFG-PCFG.pptx

915.7 KB

slides_Parsing-04-CFG-PCFG.pdf

822.4 KB

slides_Parsing-05-Grammar-Transforms.pptx

751.4 KB

slides_Parsing-08-Constituency-Evaluation.pptx

742.9 KB

slides_Parsing-05-Grammar-Transforms.pdf

742.2 KB

slides_Parsing-08-Constituency-Evaluation.pdf

702.8 KB

slides_Parsing-07-CKY-example.pptx

693.9 KB

slides_Parsing-06-CKY-introduction.pdf

668.1 KB

slides_Parsing-06-CKY-introduction.pptx

647.3 KB

slides_Parsing-07-CKY-example.pdf

641.8 KB

15 - 3 - CKY Parsing (23_25).srt

26.4 KB

15 - 4 - CKY Example (21_52).srt

23.8 KB

15 - 1 - CFGs and PCFGs (15_29).srt

18.7 KB

15 - 3 - CKY Parsing (23_25).txt

18.0 KB

15 - 4 - CKY Example (21_52).txt

16.3 KB

15 - 2 - Grammar Transforms (12_05).srt

15.6 KB

15 - 1 - CFGs and PCFGs (15_29).txt

12.8 KB

15 - 5 - Constituency Parser Evaluation (9_45).srt

12.1 KB

15 - 2 - Grammar Transforms (12_05).txt

10.7 KB

15 - 5 - Constituency Parser Evaluation (9_45).txt

8.3 KB

/14 - Week 5 - Instructor Chat/

14 - 1 - Instructor Chat (9_02).mp4

24.9 MB

/16 - Week 6 - Lexicalized Parsing/

16 - 4 - The Return of Unlexicalized PCFGs (20_53).mp4

22.2 MB

16 - 2 - Charniak's Model (18_23).mp4

19.9 MB

16 - 5 - Latent Variable PCFGs (12_07).mp4

13.2 MB

16 - 3 - PCFG Independence Assumptions (9_44).mp4

10.3 MB

16 - 1 - Lexicalization of PCFGs (7_03).mp4

7.5 MB

slides_Parsing-12-PCFGs-Unlexicalized-Return.pptx

1.4 MB

slides_Parsing-10-LPCFGs-Charniak-Model.pptx

1.0 MB

slides_Parsing-11-PCFGs-Independence.pptx

925.6 KB

slides_Parsing-13-PCFGs-Latent-Vars.pptx

890.1 KB

slides_Parsing-13-PCFGs-Latent-Vars.pdf

887.9 KB

slides_Parsing-12-PCFGs-Unlexicalized-Return.pdf

875.4 KB

slides_Parsing-09-LPCFGs-Intro.pptx

850.8 KB

slides_Parsing-10-LPCFGs-Charniak-Model.pdf

848.9 KB

slides_Parsing-11-PCFGs-Independence.pdf

691.3 KB

slides_Parsing-09-LPCFGs-Intro.pdf

668.1 KB

16 - 4 - The Return of Unlexicalized PCFGs (20_53).srt

24.6 KB

16 - 2 - Charniak's Model (18_23).srt

22.5 KB

16 - 4 - The Return of Unlexicalized PCFGs (20_53).txt

16.8 KB

16 - 2 - Charniak's Model (18_23).txt

15.4 KB

16 - 5 - Latent Variable PCFGs (12_07).srt

15.0 KB

16 - 3 - PCFG Independence Assumptions (9_44).srt

11.8 KB

16 - 5 - Latent Variable PCFGs (12_07).txt

10.2 KB

16 - 1 - Lexicalization of PCFGs (7_03).srt

8.4 KB

16 - 3 - PCFG Independence Assumptions (9_44).txt

8.1 KB

16 - 1 - Lexicalization of PCFGs (7_03).txt

5.7 KB

/18 - Week 7 - Information Retrieval/

18 - 5 - Phrase Queries and Positional Indexes (19_45).mp4

21.6 MB

18 - 3 - The Inverted Index (10_42).mp4

11.2 MB

18 - 1 - Introduction to Information Retrieval (9_16).mp4

9.5 MB

18 - 2 - Term-Document Incidence Matrices (8_59).mp4

9.5 MB

18 - 4 - Query Processing with the Inverted Index (6_43).mp4

7.1 MB

slides_05-01-02-IR-TermDocIncidence.pdf

779.2 KB

slides_05-01-02-IR-TermDocIncidence.pptx

706.9 KB

slides_05-01-03-IR-InvertedIndex.pptx

408.8 KB

slides_05-01-03-IR-InvertedIndex.pdf

297.7 KB

slides_05-01-01-IR-Introduction.pdf

217.6 KB

slides_05-01-04-IR-InvIndexQueryProcessing.pdf

181.8 KB

slides_05-01-04-IR-InvIndexQueryProcessing.pptx

163.7 KB

slides_05-01-06-IR-PhraseQueries.pdf

142.8 KB

slides_05-01-01-IR-Introduction.pptx

138.6 KB

slides_05-01-06-IR-PhraseQueries.pptx

89.6 KB

18 - 5 - Phrase Queries and Positional Indexes (19_45).srt

23.6 KB

18 - 5 - Phrase Queries and Positional Indexes (19_45).txt

16.3 KB

18 - 3 - The Inverted Index (10_42).srt

13.4 KB

18 - 1 - Introduction to Information Retrieval (9_16).srt

12.4 KB

18 - 2 - Term-Document Incidence Matrices (8_59).srt

11.0 KB

18 - 3 - The Inverted Index (10_42).txt

9.2 KB

18 - 1 - Introduction to Information Retrieval (9_16).txt

8.5 KB

18 - 2 - Term-Document Incidence Matrices (8_59).txt

7.5 KB

18 - 4 - Query Processing with the Inverted Index (6_43).srt

7.5 KB

18 - 4 - Query Processing with the Inverted Index (6_43).txt

5.2 KB

/20 - Week 8.1 - Semantics/

20 - 3 - Word Similarity and Thesaurus Methods (16_17).mp4

21.2 MB

20 - 4 - Word Similarity_ Distributional Similarity I (13_14).mp4

15.8 MB

20 - 1 - Word Senses and Word Relations (11_50).mp4

15.6 MB

20 - 5 - Word Similarity_ Distributional Similarity II (8_15).mp4

9.9 MB

20 - 2 - WordNet and Other Online Thesauri (6_23).mp4

9.2 MB

slides_07-04-Word-Similarity-Distributional-Similarity-I.pptx

2.3 MB

slides_07-02-WordNet-and-Other-Online-Thesauri.pptx

1.5 MB

slides_07-04-Word-Similarity-Distributional-Similarity-I.pdf

1.3 MB

slides_07-02-WordNet-and-Other-Online-Thesauri.pdf

1.2 MB

slides_07-03-Word-Similarity-Thesaurus-Methods.pptx

1.1 MB

slides_07-05-Word-Similarity-Distributional-Similarity-II.pptx

1.1 MB

slides_07-03-Word-Similarity-Thesaurus-Methods.pdf

909.3 KB

slides_07-05-Word-Similarity-Distributional-Similarity-II.pdf

789.1 KB

slides_07-01-Word-Senses-and-Word-Relations.pptx

681.4 KB

slides_07-01-Word-Senses-and-Word-Relations.pdf

645.2 KB

20 - 3 - Word Similarity and Thesaurus Methods (16_17).srt

23.4 KB

20 - 4 - Word Similarity_ Distributional Similarity I (13_14).srt

17.9 KB

20 - 3 - Word Similarity and Thesaurus Methods (16_17).txt

15.9 KB

20 - 1 - Word Senses and Word Relations (11_50).srt

15.6 KB

20 - 4 - Word Similarity_ Distributional Similarity I (13_14).txt

12.2 KB

20 - 5 - Word Similarity_ Distributional Similarity II (8_15).srt

11.3 KB

20 - 1 - Word Senses and Word Relations (11_50).txt

10.6 KB

20 - 2 - WordNet and Other Online Thesauri (6_23).srt

7.9 KB

20 - 5 - Word Similarity_ Distributional Similarity II (8_15).txt

7.8 KB

20 - 2 - WordNet and Other Online Thesauri (6_23).txt

5.3 KB

/07 - Week 3 - Sentiment Analysis/

7 - 4 - Learning Sentiment Lexicons (14_45).mp4

19.6 MB

7 - 5 - Other Sentiment Tasks (11_01).mp4

15.2 MB

7 - 2 - Sentiment Analysis_ A baseline algorithm (13_27).mp4

13.8 MB

7 - 3 - Sentiment Lexicons (8_37).mp4

11.1 MB

7 - 1 - What is Sentiment Analysis_ (7_17).mp4

10.0 MB

slides_03-02-WhatIsSentiment.pptx

1.7 MB

slides_03-02-WhatIsSentiment.pdf

1.2 MB

slides_03-02-LearningSALexicons.pptx

1.2 MB

slides_03-02-baselineSA.pptx

880.4 KB

slides_03-02-LearningSALexicons.pdf

845.5 KB

slides_03-02-SentimentLexicons.pptx

798.3 KB

slides_03-02-baselineSA.pdf

783.0 KB

slides_03-02-SentimentLexicons.pdf

774.5 KB

slides_03-02-OtherSentimentTasks.pdf

667.9 KB

slides_03-02-OtherSentimentTasks.pptx

663.5 KB

7 - 4 - Learning Sentiment Lexicons (14_45).srt

20.4 KB

7 - 2 - Sentiment Analysis_ A baseline algorithm (13_27).srt

18.5 KB

7 - 5 - Other Sentiment Tasks (11_01).srt

15.0 KB

7 - 4 - Learning Sentiment Lexicons (14_45).txt

14.0 KB

7 - 2 - Sentiment Analysis_ A baseline algorithm (13_27).txt

12.7 KB

7 - 3 - Sentiment Lexicons (8_37).srt

11.2 KB

7 - 5 - Other Sentiment Tasks (11_01).txt

10.3 KB

7 - 1 - What is Sentiment Analysis_ (7_17).srt

9.5 KB

7 - 3 - Sentiment Lexicons (8_37).txt

7.7 KB

7 - 1 - What is Sentiment Analysis_ (7_17).txt

6.5 KB

/23 - Week 8 - Instructor Chat II/

23 - 1 - Instructor Chat II (5_23).mp4

19.5 MB

23 - 1 - Instructor Chat II (5_23).srt

9.4 KB

23 - 1 - Instructor Chat II (5_23).txt

6.1 KB

/05 - Week 2 - Spelling Correction/

5 - 2 - The Noisy Channel Model of Spelling (19_30).mp4

18.7 MB

5 - 3 - Real-Word Spelling Correction (9_19).mp4

9.0 MB

5 - 4 - State of the Art Systems (7_10).mp4

6.9 MB

5 - 1 - The Spelling Correction Task (5_39).mp4

5.1 MB

slides_02-02-noisychannel.pdf

1.1 MB

slides_02-02-noisychannel.pptx

1.0 MB

slides_02-02-spellCorrectionTask.pptx

940.4 KB

slides_02-02-StateoftheArtSystems.pptx

857.8 KB

slides_02-02-realWorldSpellCorrect.pptx

837.7 KB

slides_02-02-realWorldSpellCorrect.pdf

804.3 KB

slides_02-02-spellCorrectionTask.pdf

771.9 KB

slides_02-02-StateoftheArtSystems.pdf

590.0 KB

5 - 2 - The Noisy Channel Model of Spelling (19_30).srt

31.6 KB

5 - 2 - The Noisy Channel Model of Spelling (19_30).txt

17.8 KB

5 - 3 - Real-Word Spelling Correction (9_19).srt

12.1 KB

5 - 4 - State of the Art Systems (7_10).srt

10.2 KB

5 - 3 - Real-Word Spelling Correction (9_19).txt

8.3 KB

5 - 1 - The Spelling Correction Task (5_39).srt

8.0 KB

5 - 4 - State of the Art Systems (7_10).txt

7.0 KB

5 - 1 - The Spelling Correction Task (5_39).txt

5.5 KB

/19 - Week 7 - Ranked Information Retrieval/

19 - 6 - The Vector Space Model (16_22).mp4

17.8 MB

19 - 7 - Calculating TF-IDF Cosine Scores (12_47).mp4

13.9 MB

19 - 4 - Inverse Document Frequency Weighting (10_16).mp4

11.7 MB

19 - 8 - Evaluating Search Engines (9_02).mp4

9.2 MB

19 - 3 - Term Frequency Weighting (5_59).mp4

6.7 MB

19 - 2 - Scoring with the Jaccard Coefficient (5_06).mp4

5.7 MB

19 - 1 - Introducing Ranked Retrieval (4_27).mp4

4.8 MB

19 - 5 - TF-IDF Weighting (3_42).mp4

4.3 MB

slides_05-02-06-IR-VectorSpaceModel.pdf

258.6 KB

slides_05-02-06-IR-VectorSpaceModel.pptx

205.2 KB

slides_05-02-03-IR-TermFreqWeighting.pdf

189.5 KB

slides_05-02-07-IR-CosineScore.pdf

163.8 KB

slides_05-02-07-IR-CosineScore.pptx

143.9 KB

slides_05-02-04-IR-IDFWeighting.pdf

141.4 KB

slides_05-02-05-IR-TFIDF.pdf

136.1 KB

slides_05-02-05-IR-TFIDF.pptx

102.9 KB

slides_05-02-03-IR-TermFreqWeighting.pptx

96.1 KB

slides_05-02-04-IR-IDFWeighting.pptx

93.0 KB

slides_05-02-09-IR-EvalSearchEngines-abridged.pdf

92.3 KB

slides_05-02-02-IR-JaccardCoefficient.pdf

84.3 KB

slides_05-02-01-IR-IntroRankedRetrieval.pptx

78.8 KB

slides_05-02-01-IR-IntroRankedRetrieval.pdf

77.6 KB

slides_05-02-02-IR-JaccardCoefficient.pptx

68.6 KB

slides_05-02-09-IR-EvalSearchEngines-abridged.pptx

64.5 KB

19 - 6 - The Vector Space Model (16_22).srt

20.1 KB

19 - 7 - Calculating TF-IDF Cosine Scores (12_47).srt

15.8 KB

19 - 6 - The Vector Space Model (16_22).txt

13.7 KB

19 - 4 - Inverse Document Frequency Weighting (10_16).srt

12.7 KB

19 - 8 - Evaluating Search Engines (9_02).srt

11.5 KB

19 - 7 - Calculating TF-IDF Cosine Scores (12_47).txt

10.8 KB

19 - 4 - Inverse Document Frequency Weighting (10_16).txt

8.7 KB

19 - 8 - Evaluating Search Engines (9_02).txt

7.9 KB

19 - 3 - Term Frequency Weighting (5_59).srt

7.5 KB

19 - 2 - Scoring with the Jaccard Coefficient (5_06).srt

6.2 KB

19 - 1 - Introducing Ranked Retrieval (4_27).srt

6.1 KB

19 - 3 - Term Frequency Weighting (5_59).txt

5.2 KB

19 - 2 - Scoring with the Jaccard Coefficient (5_06).txt

4.3 KB

19 - 5 - TF-IDF Weighting (3_42).srt

4.2 KB

19 - 1 - Introducing Ranked Retrieval (4_27).txt

4.2 KB

19 - 5 - TF-IDF Weighting (3_42).txt

2.9 KB

/08 - Week 4 - Discriminative classifiers Maximum Entropy classifiers/

8 - 2 - Making features from text for discriminative NLP models (18_11).mp4

17.5 MB

8 - 3 - Feature-Based Linear Classifiers (13_34).mp4

14.1 MB

8 - 5 - Generative vs. Discriminative models_ The problem of overcounting evidence (12_15).mp4

12.8 MB

8 - 6 - Maximizing the Likelihood (10_29).mp4

10.3 MB

8 - 1 - Generative vs. Discriminative Models (7_49).mp4

8.3 MB

8 - 4 - Building a Maxent Model_ The Nuts and Bolts (8_04).mp4

8.2 MB

slides_04-01-Maximizing_the_Likelihood.pdf

1.5 MB

slides_04-01-Maximizing_the_Likelihood.pptx

1.5 MB

slides_04-01-Feature-based_Linear_Classifiers.pdf

804.9 KB

slides_04-01-Feature-based_Linear_Classifiers.pptx

773.2 KB

slides_04-01-Discriminative_Model_Features.pdf

748.2 KB

slides_04-01-Discriminative_Model_Features.pptx

695.7 KB

slides_04-01-Building_a_Maxent_Model.pdf

651.5 KB

slides_04-01-Generative_vs_Distriminative_Models.pdf

635.9 KB

slides_04-01-Generative_vs._Discriminative_Models-The_Problem_of_Overcounting_Evidence.pptx

633.3 KB

slides_04-01-Generative_vs_Distriminative_Models.pptx

623.2 KB

slides_04-01-Building_a_Maxent_Model.pptx

610.5 KB

slides_04-01-Generative_vs._Discriminative_Models-The_Problem_of_Overcounting_Evidence.pdf

606.7 KB

8 - 2 - Making features from text for discriminative NLP models (18_11).srt

22.4 KB

8 - 3 - Feature-Based Linear Classifiers (13_34).srt

16.0 KB

8 - 2 - Making features from text for discriminative NLP models (18_11).txt

15.3 KB

8 - 5 - Generative vs. Discriminative models_ The problem of overcounting evidence (12_15).srt

14.6 KB

8 - 6 - Maximizing the Likelihood (10_29).srt

12.8 KB

8 - 3 - Feature-Based Linear Classifiers (13_34).txt

11.0 KB

8 - 1 - Generative vs. Discriminative Models (7_49).srt

10.1 KB

8 - 5 - Generative vs. Discriminative models_ The problem of overcounting evidence (12_15).txt

10.0 KB

8 - 4 - Building a Maxent Model_ The Nuts and Bolts (8_04).srt

9.7 KB

8 - 6 - Maximizing the Likelihood (10_29).txt

8.8 KB

8 - 1 - Generative vs. Discriminative Models (7_49).txt

6.9 KB

8 - 4 - Building a Maxent Model_ The Nuts and Bolts (8_04).txt

6.6 KB

/06 - Week 3 - Text Classification/

6 - 7 - Precision, Recall, and the F measure (16_16).mp4

16.5 MB

6 - 8 - Text Classification_ Evaluation (7_17).mp4

12.1 MB

6 - 6 - Multinomial Naive Bayes_ A Worked Example (8_58).mp4

11.9 MB

6 - 3 - Formalizing the Naive Bayes Classifier (9_28).mp4

8.6 MB

6 - 1 - What is Text Classification_ (8_12).mp4

8.1 MB

6 - 9 - Practical Issues in Text Classification (5_56).mp4

6.9 MB

6 - 4 - Naive Bayes_ Learning (5_22).mp4

6.5 MB

6 - 5 - Naive Bayes_ Relationship to Language Modeling (4_35).mp4

4.3 MB

6 - 2 - Naive Bayes (3_19).mp4

3.4 MB

slides_03-01-NBLearning.pptx

1.2 MB

slides_03-01-FormalizingNB.pptx

1.1 MB

slides_03-01-FormalizingNB.pdf

1.1 MB

slides_03-01-taskTextClass.pptx

917.5 KB

slides_03-01-NBLearning.pdf

834.2 KB

slides_03-01-taskTextClass.pdf

800.4 KB

slides_03-01-textClassPractical.pptx

766.5 KB

slides_03-01-MultinomNBexample.pptx

724.0 KB

slides_03-01-textClassEval.pptx

720.1 KB

slides_03-01-textClassEval.pdf

708.3 KB

slides_03-01-textClassPractical.pdf

690.0 KB

slides_03-01-NaiveBayes.pdf

679.5 KB

slides_03-01-precisionRecallFmeasure.pptx

678.8 KB

slides_03-01-NaiveBayes.pptx

669.7 KB

slides_03-01-NBRelationLM.pptx

657.0 KB

slides_03-01-MultinomNBexample.pdf

648.0 KB

slides_03-01-NBRelationLM.pdf

643.3 KB

slides_03-01-precisionRecallFmeasure.pdf

638.2 KB

6 - 7 - Precision, Recall, and the F measure (16_16).srt

18.5 KB

6 - 7 - Precision, Recall, and the F measure (16_16).txt

12.7 KB

6 - 3 - Formalizing the Naive Bayes Classifier (9_28).srt

12.0 KB

6 - 8 - Text Classification_ Evaluation (7_17).srt

11.2 KB

6 - 6 - Multinomial Naive Bayes_ A Worked Example (8_58).srt

10.6 KB

6 - 1 - What is Text Classification_ (8_12).srt

10.5 KB

6 - 9 - Practical Issues in Text Classification (5_56).srt

8.7 KB

6 - 3 - Formalizing the Naive Bayes Classifier (9_28).txt

8.2 KB

6 - 4 - Naive Bayes_ Learning (5_22).srt

8.1 KB

6 - 8 - Text Classification_ Evaluation (7_17).txt

7.6 KB

6 - 6 - Multinomial Naive Bayes_ A Worked Example (8_58).txt

7.3 KB

6 - 1 - What is Text Classification_ (8_12).txt

7.2 KB

6 - 5 - Naive Bayes_ Relationship to Language Modeling (4_35).srt

6.1 KB

6 - 9 - Practical Issues in Text Classification (5_56).txt

6.0 KB

6 - 4 - Naive Bayes_ Learning (5_22).txt

4.9 KB

6 - 2 - Naive Bayes (3_19).srt

4.6 KB

6 - 5 - Naive Bayes_ Relationship to Language Modeling (4_35).txt

4.2 KB

6 - 2 - Naive Bayes (3_19).txt

3.2 KB

/12 - Week 5 - POS Tagging/

13 - 3 - The Exponential Problem in Parsing (14_30).mp4

15.6 MB

12 - 2 - Some Methods and Results on Sequence Models for POS Tagging (13_04).mp4

13.4 MB

12 - 1 - An Intro to Parts of Speech and POS Tagging (13_19).mp4

12.5 MB

slides_05-06-PosTagging_Models.pdf

668.4 KB

slides_05-05-PosTagging_Intro.pdf

666.0 KB

slides_05-05-PosTagging_Intro.pptx

634.1 KB

slides_05-06-PosTagging_Models.pptx

625.2 KB

12 - 1 - An Intro to Parts of Speech and POS Tagging (13_19).srt

17.9 KB

12 - 2 - Some Methods and Results on Sequence Models for POS Tagging (13_04).srt

17.3 KB

12 - 1 - An Intro to Parts of Speech and POS Tagging (13_19).txt

12.3 KB

12 - 2 - Some Methods and Results on Sequence Models for POS Tagging (13_04).txt

11.9 KB

/13 - Week 5 - Parsing Introduction/

13 - 3 - The Exponential Problem in Parsing (14_30).mp4

15.6 MB

13 - 1 - Syntactic Structure_ Constituency vs Dependency (8_46).mp4

9.4 MB

13 - 2 - Empirical_Data-Driven Approach to Parsing (7_11).mp4

7.6 MB

slides_Parsing-03-Exponential-Problems.pptx

794.4 KB

slides_Parsing-01-Constituency-Dependency.pdf

748.4 KB

slides_Parsing-03-Exponential-Problems.pdf

743.6 KB

slides_Parsing-01-Constituency-Dependency.pptx

711.4 KB

slides_Parsing-02-Why-Empirical.pptx

660.1 KB

slides_Parsing-02-Why-Empirical.pdf

622.5 KB

13 - 3 - The Exponential Problem in Parsing (14_30).srt

17.3 KB

13 - 3 - The Exponential Problem in Parsing (14_30).txt

11.9 KB

13 - 1 - Syntactic Structure_ Constituency vs Dependency (8_46).srt

10.8 KB

13 - 2 - Empirical_Data-Driven Approach to Parsing (7_11).srt

9.4 KB

13 - 1 - Syntactic Structure_ Constituency vs Dependency (8_46).txt

7.4 KB

13 - 2 - Empirical_Data-Driven Approach to Parsing (7_11).txt

6.5 KB

/09 - Week 4 - Named entity recognition and Maximum Entropy Sequence Models/

9 - 3 - Sequence Models for Named Entity Recognition (15_05).mp4

14.8 MB

9 - 4 - Maximum Entropy Sequence Models (13_01).mp4

13.9 MB

9 - 1 - Introduction to Information Extraction (9_18).mp4

9.8 MB

9 - 2 - Evaluation of Named Entity Recognition (6_34).mp4

7.1 MB

slides_04-02-Sequence_Models_for_Named_Entity_Recognition.pdf

756.5 KB

slides_04-02-Introducing_the_Tasks-v2.pptx

746.9 KB

slides_04-02-Maximum_Entropy_Sequence_Models-v2.pdf

735.0 KB

slides_04-02-Sequence_Models_for_Named_Entity_Recognition.pptx

727.0 KB

slides_04-02-Maximum_Entropy_Sequence_Models-v2.pptx

722.9 KB

slides_04-02-Introducing_the_Tasks-v2.pdf

679.2 KB

slides_04-02-Evaluation_of_Named_Entity_Recognition-v2.pptx

612.3 KB

slides_04-02-Evaluation_of_Named_Entity_Recognition-v2.pdf

583.7 KB

9 - 3 - Sequence Models for Named Entity Recognition (15_05).srt

18.4 KB

9 - 4 - Maximum Entropy Sequence Models (13_01).srt

17.1 KB

9 - 3 - Sequence Models for Named Entity Recognition (15_05).txt

12.6 KB

9 - 1 - Introduction to Information Extraction (9_18).srt

11.9 KB

9 - 4 - Maximum Entropy Sequence Models (13_01).txt

11.7 KB

9 - 1 - Introduction to Information Extraction (9_18).txt

8.2 KB

9 - 2 - Evaluation of Named Entity Recognition (6_34).srt

7.7 KB

9 - 2 - Evaluation of Named Entity Recognition (6_34).txt

5.3 KB

/04 - Week 2 - Language Modeling/

4 - 7 - Good-Turing Smoothing (15_35).mp4

14.1 MB

4 - 3 - Evaluation and Perplexity (11_09).mp4

10.1 MB

4 - 2 - Estimating N-gram Probabilities (9_38).mp4

9.9 MB

4 - 6 - Interpolation (10_25).mp4

9.8 MB

4 - 8 - Kneser-Ney Smoothing (8_59).mp4

8.8 MB

4 - 1 - Introduction to N-grams (8_41).mp4

8.0 MB

4 - 5 - Smoothing_ Add-One (6_30).mp4

6.3 MB

4 - 4 - Generalization and Zeros (5_15).mp4

4.9 MB

slides_02-01-advKnesNeySmooth.pptx

1.2 MB

slides_02-01-advGoodTuringSmooth.pptx

996.5 KB

slides_02-01-estimNgramProbs.pptx

965.1 KB

slides_02-01-smoothingAddone.pptx

921.6 KB

slides_02-01-interpBackoff.pptx

889.7 KB

slides_02-01-ngramIntro.pptx

871.9 KB

slides_02-01-generalization.pptx

870.9 KB

slides_02-01-smoothingAddone.pdf

860.8 KB

slides_02-01-generalization.pdf

850.5 KB

slides_02-01-advKnesNeySmooth.pdf

836.8 KB

slides_02-01-estimNgramProbs.pdf

830.0 KB

slides_02-01-advGoodTuringSmooth.pdf

794.4 KB

slides_02-01-ngramIntro.pdf

766.6 KB

slides_02-01-interpBackoff.pdf

757.2 KB

slides_02-01-EvalandPerplex.pptx

690.3 KB

slides_02-01-EvalandPerplex.pdf

634.4 KB

4 - 7 - Good-Turing Smoothing (15_35).srt

20.4 KB

4 - 3 - Evaluation and Perplexity (11_09).srt

15.5 KB

4 - 7 - Good-Turing Smoothing (15_35).txt

14.0 KB

4 - 6 - Interpolation (10_25).srt

14.0 KB

4 - 8 - Kneser-Ney Smoothing (8_59).srt

13.4 KB

4 - 1 - Introduction to N-grams (8_41).srt

12.3 KB

4 - 2 - Estimating N-gram Probabilities (9_38).srt

12.0 KB

4 - 3 - Evaluation and Perplexity (11_09).txt

10.6 KB

4 - 6 - Interpolation (10_25).txt

9.6 KB

4 - 8 - Kneser-Ney Smoothing (8_59).txt

9.0 KB

4 - 1 - Introduction to N-grams (8_41).txt

8.4 KB

4 - 2 - Estimating N-gram Probabilities (9_38).txt

8.3 KB

4 - 5 - Smoothing_ Add-One (6_30).srt

8.2 KB

4 - 4 - Generalization and Zeros (5_15).srt

7.2 KB

4 - 5 - Smoothing_ Add-One (6_30).txt

5.6 KB

4 - 4 - Generalization and Zeros (5_15).txt

5.0 KB

/22 - Week 8 - Summarization/

22 - 4 - Summarizing Multiple Documents.mp4

14.1 MB

22 - 2 - Generating Snippets.mp4

10.1 MB

22 - 3 - Evaluating Summaries_ ROUGE.mp4

6.8 MB

22 - 1 - Introduction to Summarization.mp4

6.3 MB

slides_08-Summarization-02-Snippets.pptx

1.1 MB

slides_08-Summarization-04-Multiple.pptx

1.1 MB

slides_08-Summarization-04-Multiple.pdf

976.0 KB

slides_08-Summarization-02-Snippets.pdf

916.2 KB

slides_08-Summarization-01-Intro.pptx

864.8 KB

slides_08-Summarization-01-Intro.pdf

766.6 KB

slides_08-Summarization-03-Evaluation.pptx

708.3 KB

slides_08-Summarization-03-Evaluation.pdf

620.5 KB

22 - 4 - Summarizing Multiple Documents.srt

16.3 KB

22 - 2 - Generating Snippets.srt

11.6 KB

22 - 4 - Summarizing Multiple Documents.txt

11.2 KB

22 - 2 - Generating Snippets.txt

7.9 KB

22 - 1 - Introduction to Summarization.srt

7.2 KB

22 - 3 - Evaluating Summaries_ ROUGE.srt

6.6 KB

22 - 1 - Introduction to Summarization.txt

4.9 KB

22 - 3 - Evaluating Summaries_ ROUGE.txt

4.5 KB

/02 - Week 1 - Basic Text Processing/

2 - 3 - Word Tokenization (14_26).mp4

13.1 MB

2 - 1 - Regular Expressions (11_25).mp4

11.4 MB

2 - 4 - Word Normalization and Stemming (11_47).mp4

10.6 MB

2 - 2 - Regular Expressions in Practical NLP (6_04).mp4

8.4 MB

2 - 5 - Sentence Segmentation (5_31).mp4

5.2 MB

slides_01-02-regexp.pptx

714.4 KB

slides_01-02-wordtok.pdf

687.5 KB

slides_01-02-wordtok.pptx

686.4 KB

slides_01-02-sentsegment.pptx

684.9 KB

slides_01-02-normalization.pptx

673.6 KB

slides_01-02-regexp.pdf

668.0 KB

slides_01-02-normalization.pdf

631.6 KB

slides_01-02-sentsegment.pdf

625.4 KB

2 - 3 - Word Tokenization (14_26).srt

20.0 KB

2 - 1 - Regular Expressions (11_25).srt

14.8 KB

2 - 4 - Word Normalization and Stemming (11_47).srt

14.6 KB

2 - 3 - Word Tokenization (14_26).txt

13.7 KB

2 - 1 - Regular Expressions (11_25).txt

10.1 KB

2 - 4 - Word Normalization and Stemming (11_47).txt

10.0 KB

2 - 2 - Regular Expressions in Practical NLP (6_04).srt

7.9 KB

2 - 5 - Sentence Segmentation (5_31).srt

7.8 KB

2 - 2 - Regular Expressions in Practical NLP (6_04).txt

5.4 KB

2 - 5 - Sentence Segmentation (5_31).txt

5.3 KB

/01 - Week 1 - Course Introduction/

1 - 1 - Course Introduction (14_11).mp4

12.9 MB

intro.pdf

2.8 MB

slides_intro.pdf

2.8 MB

intro.pptx

2.1 MB

slides_intro.pptx

2.1 MB

1 - 1 - Course Introduction (14_11).srt

18.8 KB

1 - 1 - Course Introduction (14_11).txt

12.8 KB

/10 - Week 4 - Relation Extraction/

10 - 3 - Supervised Relation Extraction (10_51).mp4

10.8 MB

10 - 1 - What is Relation Extraction_ (9_47).mp4

10.7 MB

10 - 4 - Semi-Supervised and Unsupervised Relation Extraction (9_53).mp4

10.6 MB

10 - 2 - Using Patterns to Extract Relations (6_17).mp4

6.4 MB

slides_06-08-Supervised-Relation-Extraction-v2.pdf

4.1 MB

slides_06-09-Semi-Supervised-and-Unsupervised-Relation-Extraction-v2.pdf

3.5 MB

slides_06-07-Using-Patterns-To-Extract-Relations-v2.pdf

3.2 MB

slides_06-06-What-Is-Relation-Extraction-.pptx

1.4 MB

slides_06-06-What-Is-Relation-Extraction-v2.pdf

1.2 MB

slides_06-08-Supervised-Relation-Extraction.pptx

913.2 KB

slides_06-07-Using-Patterns-To-Extract-Relations.pptx

763.7 KB

slides_06-09-Semi-Supervised-and-Unsupervised-Relation-Extraction.pptx

716.9 KB

10 - 3 - Supervised Relation Extraction (10_51).srt

16.6 KB

10 - 4 - Semi-Supervised and Unsupervised Relation Extraction (9_53).srt

14.8 KB

10 - 1 - What is Relation Extraction_ (9_47).srt

13.8 KB

10 - 3 - Supervised Relation Extraction (10_51).txt

11.4 KB

10 - 4 - Semi-Supervised and Unsupervised Relation Extraction (9_53).txt

10.1 KB

10 - 1 - What is Relation Extraction_ (9_47).txt

9.4 KB

10 - 2 - Using Patterns to Extract Relations (6_17).srt

9.2 KB

10 - 2 - Using Patterns to Extract Relations (6_17).txt

6.3 KB

/21 - Week 8 - Question Answering/

21 - 2 - Answer Types and Query Formulation (8_47).mp4

10.6 MB

21 - 1 - What is Question Answering_ (7_28).mp4

9.3 MB

21 - 3 - Passage Retrieval and Answer Extraction (6_38).mp4

8.1 MB

21 - 5 - Advanced_ Answering Complex Questions (4_52).mp4

6.5 MB

21 - 4 - Using Knowledge in QA (4_25).mp4

5.5 MB

slides_07-06-What-is-Question-Answering.pptx

1.2 MB

slides_07-07-Answer-Types-and-Query-Formulation.pptx

1.1 MB

slides_07-07-Answer-Types-and-Query-Formulation.pdf

985.2 KB

slides_07-06-What-is-Question-Answering.pdf

979.9 KB

slides_07-08-Passage-Retrieval-and-Answer-Extraction.pptx

841.4 KB

slides_07-10-Advanced-Answering-Complex-Questions.pptx

838.8 KB

slides_07-09-Using-Knowledge-In-QA.pptx

783.2 KB

slides_07-08-Passage-Retrieval-and-Answer-Extraction.pdf

739.9 KB

slides_07-10-Advanced-Answering-Complex-Questions.pdf

727.4 KB

slides_07-09-Using-Knowledge-In-QA.pdf

682.2 KB

21 - 2 - Answer Types and Query Formulation (8_47).srt

12.8 KB

21 - 1 - What is Question Answering_ (7_28).srt

10.6 KB

21 - 3 - Passage Retrieval and Answer Extraction (6_38).srt

9.7 KB

21 - 2 - Answer Types and Query Formulation (8_47).txt

8.8 KB

21 - 1 - What is Question Answering_ (7_28).txt

7.3 KB

21 - 5 - Advanced_ Answering Complex Questions (4_52).srt

7.0 KB

21 - 3 - Passage Retrieval and Answer Extraction (6_38).txt

6.7 KB

21 - 4 - Using Knowledge in QA (4_25).srt

6.6 KB

21 - 5 - Advanced_ Answering Complex Questions (4_52).txt

4.8 KB

21 - 4 - Using Knowledge in QA (4_25).txt

4.5 KB

/03 - Week 1 - Edit Distance/

3 - 5 - Minimum Edit Distance in Computational Biology (9_29).mp4

9.4 MB

3 - 1 - Defining Minimum Edit Distance (7_04).mp4

6.9 MB

3 - 3 - Backtrace for Computing Alignments (5_55).mp4

5.8 MB

3 - 2 - Computing Minimum Edit Distance (5_54).mp4

5.6 MB

3 - 4 - Weighted Minimum Edit Distance (2_47).mp4

3.0 MB

slides_01-03-weighted.pptx

944.9 KB

slides_01-03-weighted.pdf

938.2 KB

slides_01-03-backtrace.pptx

787.8 KB

slides_01-03-backtrace.pdf

728.7 KB

slides_01-03-defineMinEdit.pptx

716.2 KB

slides_01-03-combio.pptx

714.8 KB

slides_01-03-computingmineditdistance.pptx

710.3 KB

slides_01-03-combio.pdf

689.1 KB

slides_01-03-defineMinEdit.pdf

662.4 KB

slides_01-03-computingmineditdistance.pdf

625.2 KB

3 - 5 - Minimum Edit Distance in Computational Biology (9_29).srt

11.3 KB

3 - 1 - Defining Minimum Edit Distance (7_04).srt

9.0 KB

3 - 5 - Minimum Edit Distance in Computational Biology (9_29).txt

7.8 KB

3 - 3 - Backtrace for Computing Alignments (5_55).srt

7.2 KB

3 - 2 - Computing Minimum Edit Distance (5_54).srt

6.8 KB

3 - 1 - Defining Minimum Edit Distance (7_04).txt

6.2 KB

3 - 3 - Backtrace for Computing Alignments (5_55).txt

4.9 KB

3 - 2 - Computing Minimum Edit Distance (5_54).txt

4.7 KB

3 - 4 - Weighted Minimum Edit Distance (2_47).srt

3.9 KB

3 - 4 - Weighted Minimum Edit Distance (2_47).txt

2.6 KB

 

Total files 505


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