[Coursera] Natural Language Processing (Dan Jurafsky and Chris Manning)
Dan Jurafsky and Chris Manning

Info hash9ad3c282ff6c4137ed8b073d884ea3d72c2e4cd1
Last mirror activity3:19 ago
Size1.18GB (1,176,932,543 bytes)
Added2020-06-08 18:24:26
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ID4528
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FolderNatural Language Processing
Num files102 files
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1 - 1 - Course Introduction (14_11).mp412.85MB
10 - 1 - What is Relation Extraction_ (9_47).mp410.68MB
10 - 2 - Using Patterns to Extract Relations (6_17).mp46.37MB
10 - 3 - Supervised Relation Extraction (10_51).mp410.81MB
10 - 4 - Semi-Supervised and Unsupervised Relation Extraction (9_53).mp410.55MB
11 - 1 - The Maximum Entropy Model Presentation (12_14).mp418.12MB
11 - 2 - Feature Overlap_Feature Interaction (12_51).mp413.25MB
11 - 3 - Conditional Maxent Models for Classification (4_11).mp45.02MB
11 - 4 - Smoothing_Regularization_Priors for Maxent Models (29_24).mp430.19MB
12 - 1 - An Intro to Parts of Speech and POS Tagging (13_19).mp412.46MB
12 - 2 - Some Methods and Results on Sequence Models for POS Tagging (13_04).mp413.44MB
13 - 1 - Syntactic Structure_ Constituency vs Dependency (8_46).mp49.40MB
13 - 2 - Empirical_Data-Driven Approach to Parsing (7_11).mp47.59MB
13 - 3 - The Exponential Problem in Parsing (14_30).mp415.59MB
14 - 1 - Instructor Chat (9_02).mp424.93MB
15 - 1 - CFGs and PCFGs (15_29).mp417.45MB
15 - 2 - Grammar Transforms (12_05).mp412.63MB
15 - 3 - CKY Parsing (23_25).mp427.45MB
15 - 4 - CKY Example (21_52).mp424.58MB
15 - 5 - Constituency Parser Evaluation (9_45).mp411.18MB
16 - 1 - Lexicalization of PCFGs (7_03).mp47.47MB
16 - 2 - Charniak_'s Model (18_23).mp419.88MB
16 - 3 - PCFG Independence Assumptions (9_44).mp410.31MB
16 - 4 - The Return of Unlexicalized PCFGs (20_53).mp422.25MB
16 - 5 - Latent Variable PCFGs (12_07).mp413.16MB
17 - 1 - Dependency Parsing Introduction (10_25).mp411.69MB
17 - 2 - Greedy Transition-Based Parsing (31_05).mp432.88MB
17 - 3 - Dependencies Encode Relational Structure (7_20).mp47.59MB
18 - 1 - Introduction to Information Retrieval (9_16).mp49.50MB
18 - 2 - Term-Document Incidence Matrices (8_59).mp49.46MB
18 - 3 - The Inverted Index (10_42).mp411.23MB
18 - 4 - Query Processing with the Inverted Index (6_43).mp47.07MB
18 - 5 - Phrase Queries and Positional Indexes (19_45).mp421.60MB
19 - 1 - Introducing Ranked Retrieval (4_27).mp44.80MB
19 - 2 - Scoring with the Jaccard Coefficient (5_06).mp45.66MB
19 - 3 - Term Frequency Weighting (5_59).mp46.67MB
19 - 4 - Inverse Document Frequency Weighting (10_16).mp411.66MB
19 - 5 - TF-IDF Weighting (3_42).mp44.30MB
19 - 6 - The Vector Space Model (16_22).mp417.76MB
19 - 7 - Calculating TF-IDF Cosine Scores (12_47).mp413.88MB
19 - 8 - Evaluating Search Engines (9_02).mp49.24MB
2 - 1 - Regular Expressions (11_25).mp411.37MB
2 - 2 - Regular Expressions in Practical NLP (6_04).mp48.35MB
2 - 3 - Word Tokenization (14_26).mp413.07MB
2 - 4 - Word Normalization and Stemming (11_47).mp410.57MB
2 - 5 - Sentence Segmentation (5_31).mp45.21MB
20 - 1 - Word Senses and Word Relations (11_50).mp415.62MB
20 - 2 - WordNet and Other Online Thesauri (6_23).mp49.17MB
20 - 3 - Word Similarity and Thesaurus Methods (16_17).mp421.22MB
20 - 4 - Word Similarity_ Distributional Similarity I (13_14).mp415.76MB
20 - 5 - Word Similarity_ Distributional Similarity II (8_15).mp49.92MB
21 - 1 - What is Question Answering_ (7_28).mp49.32MB
21 - 2 - Answer Types and Query Formulation (8_47).mp410.61MB
21 - 3 - Passage Retrieval and Answer Extraction (6_38).mp48.05MB
21 - 4 - Using Knowledge in QA (4_25).mp45.53MB
21 - 5 - Advanced_ Answering Complex Questions (4_52).mp46.47MB
22 - 1 - Introduction to Summarization.mp46.31MB
22 - 2 - Generating Snippets.mp410.08MB
22 - 3 - Evaluating Summaries_ ROUGE.mp46.85MB
22 - 4 - Summarizing Multiple Documents.mp414.05MB
23 - 1 - Instructor Chat II (5_23).mp419.53MB
3 - 1 - Defining Minimum Edit Distance (7_04).mp46.92MB
3 - 2 - Computing Minimum Edit Distance (5_54).mp45.65MB
3 - 3 - Backtrace for Computing Alignments (5_55).mp45.80MB
3 - 4 - Weighted Minimum Edit Distance (2_47).mp42.97MB
3 - 5 - Minimum Edit Distance in Computational Biology (9_29).mp49.38MB
4 - 1 - Introduction to N-grams (8_41).mp48.01MB
4 - 2 - Estimating N-gram Probabilities (9_38).mp49.94MB
4 - 3 - Evaluation and Perplexity (11_09).mp410.06MB
4 - 4 - Generalization and Zeros (5_15).mp44.90MB
4 - 5 - Smoothing_ Add-One (6_30).mp46.34MB
4 - 6 - Interpolation (10_25).mp49.83MB
4 - 7 - Good-Turing Smoothing (15_35).mp414.09MB
4 - 8 - Kneser-Ney Smoothing (8_59).mp48.85MB
5 - 1 - The Spelling Correction Task (5_39).mp45.08MB
5 - 2 - The Noisy Channel Model of Spelling (19_30).mp418.65MB
5 - 3 - Real-Word Spelling Correction (9_19).mp48.98MB
5 - 4 - State of the Art Systems (7_10).mp46.93MB
6 - 1 - What is Text Classification_ (8_12).mp48.08MB
6 - 2 - Naive Bayes (3_19).mp43.41MB
6 - 3 - Formalizing the Naive Bayes Classifier (9_28).mp48.58MB
6 - 4 - Naive Bayes_ Learning (5_22).mp46.49MB
6 - 5 - Naive Bayes_ Relationship to Language Modeling (4_35).mp44.29MB
6 - 6 - Multinomial Naive Bayes_ A Worked Example (8_58).mp411.94MB
6 - 7 - Precision, Recall, and the F measure (16_16).mp416.48MB
6 - 8 - Text Classification_ Evaluation (7_17).mp412.11MB
6 - 9 - Practical Issues in Text Classification (5_56).mp46.88MB
7 - 1 - What is Sentiment Analysis_ (7_17).mp410.02MB
7 - 2 - Sentiment Analysis_ A baseline algorithm (13_27).mp413.82MB
7 - 3 - Sentiment Lexicons (8_37).mp411.09MB
7 - 4 - Learning Sentiment Lexicons (14_45).mp419.56MB
7 - 5 - Other Sentiment Tasks (11_01).mp415.23MB
8 - 1 - Generative vs. Discriminative Models (7_49).mp48.31MB
8 - 2 - Making features from text for discriminative NLP models (18_11).mp417.47MB
8 - 3 - Feature-Based Linear Classifiers (13_34).mp414.11MB
8 - 4 - Building a Maxent Model_ The Nuts and Bolts (8_04).mp48.17MB
8 - 5 - Generative vs. Discriminative models_ The problem of overcounting evidence (12_15).mp412.81MB
8 - 6 - Maximizing the Likelihood (10_29).mp410.31MB
9 - 1 - Introduction to Information Extraction (9_18).mp49.85MB
9 - 2 - Evaluation of Named Entity Recognition (6_34).mp47.08MB
9 - 3 - Sequence Models for Named Entity Recognition (15_05).mp414.83MB
9 - 4 - Maximum Entropy Sequence Models (13_01).mp413.95MB
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