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| 10 - 1 - What is Relation Extraction_ (9_47).mp4 |
10.19MB |
| 10 - 2 - Using Patterns to Extract Relations (6_17).mp4 |
6.08MB |
| 10 - 3 - Supervised Relation Extraction (10_51).mp4 |
10.31MB |
| 10 - 4 - Semi-Supervised and Unsupervised Relation Extraction (9_53).mp4 |
10.06MB |
| 11 - 1 - The Maximum Entropy Model Presentation (12_14).mp4 |
17.28MB |
| 11 - 2 - Feature Overlap_Feature Interaction (12_51).mp4 |
12.63MB |
| 11 - 3 - Conditional Maxent Models for Classification (4_11).mp4 |
4.79MB |
| 11 - 4 - Smoothing_Regularization_Priors for Maxent Models (29_24).mp4 |
28.80MB |
| 1 - 1 - Course Introduction (14_11).mp4 |
12.26MB |
| 12 - 1 - An Intro to Parts of Speech and POS Tagging (13_19).mp4 |
11.88MB |
| 12 - 2 - Some Methods and Results on Sequence Models for POS Tagging (13_04).mp4 |
12.82MB |
| 13 - 1 - Syntactic Structure_ Constituency vs Dependency (8_46).mp4 |
8.96MB |
| 13 - 2 - Empirical_Data-Driven Approach to Parsing (7_11).mp4 |
7.24MB |
| 13 - 3 - The Exponential Problem in Parsing (14_30).mp4 |
14.87MB |
| 14 - 1 - Instructor Chat (9_02).mp4 |
23.78MB |
| 15 - 1 - CFGs and PCFGs (15_29).mp4 |
16.65MB |
| 15 - 2 - Grammar Transforms (12_05).mp4 |
12.05MB |
| 15 - 3 - CKY Parsing (23_25).mp4 |
26.18MB |
| 15 - 4 - CKY Example (21_52).mp4 |
23.44MB |
| 15 - 5 - Constituency Parser Evaluation (9_45).mp4 |
10.66MB |
| 16 - 1 - Lexicalization of PCFGs (7_03).mp4 |
7.12MB |
| 16 - 2 - Charniak_'s Model (18_23).mp4 |
18.96MB |
| 16 - 3 - PCFG Independence Assumptions (9_44).mp4 |
9.83MB |
| 16 - 4 - The Return of Unlexicalized PCFGs (20_53).mp4 |
21.22MB |
| 16 - 5 - Latent Variable PCFGs (12_07).mp4 |
12.55MB |
| 17 - 1 - Dependency Parsing Introduction (10_25).mp4 |
11.15MB |
| 17 - 2 - Greedy Transition-Based Parsing (31_05).mp4 |
31.36MB |
| 17 - 3 - Dependencies Encode Relational Structure (7_20).mp4 |
7.24MB |
| 18 - 1 - Introduction to Information Retrieval (9_16).mp4 |
9.06MB |
| 18 - 2 - Term-Document Incidence Matrices (8_59).mp4 |
9.02MB |
| 18 - 3 - The Inverted Index (10_42).mp4 |
10.71MB |
| 18 - 4 - Query Processing with the Inverted Index (6_43).mp4 |
6.74MB |
| 18 - 5 - Phrase Queries and Positional Indexes (19_45).mp4 |
20.60MB |
| 19 - 1 - Introducing Ranked Retrieval (4_27).mp4 |
4.58MB |
| 19 - 2 - Scoring with the Jaccard Coefficient (5_06).mp4 |
5.39MB |
| 19 - 3 - Term Frequency Weighting (5_59).mp4 |
6.36MB |
| 19 - 4 - Inverse Document Frequency Weighting (10_16).mp4 |
11.12MB |
| 19 - 5 - TF-IDF Weighting (3_42).mp4 |
4.10MB |
| 19 - 6 - The Vector Space Model (16_22).mp4 |
16.93MB |
| 19 - 7 - Calculating TF-IDF Cosine Scores (12_47).mp4 |
13.23MB |
| 19 - 8 - Evaluating Search Engines (9_02).mp4 |
8.82MB |
| 20 - 1 - Word Senses and Word Relations (11_50).mp4 |
14.89MB |
| 20 - 2 - WordNet and Other Online Thesauri (6_23).mp4 |
8.75MB |
| 20 - 3 - Word Similarity and Thesaurus Methods (16_17).mp4 |
20.24MB |
| 20 - 4 - Word Similarity_ Distributional Similarity I (13_14).mp4 |
15.03MB |
| 20 - 5 - Word Similarity_ Distributional Similarity II (8_15).mp4 |
9.46MB |
| 21 - 1 - What is Question Answering_ (7_28).mp4 |
8.89MB |
| 21 - 2 - Answer Types and Query Formulation (8_47).mp4 |
10.12MB |
| 21 - 3 - Passage Retrieval and Answer Extraction (6_38).mp4 |
7.68MB |
| 21 - 4 - Using Knowledge in QA (4_25).mp4 |
5.27MB |
| 21 - 5 - Advanced_ Answering Complex Questions (4_52).mp4 |
6.17MB |
| 2 - 1 - Regular Expressions (11_25).mp4 |
10.85MB |
| 22 - 1 - Introduction to Summarization.mp4 |
6.02MB |
| 22 - 2 - Generating Snippets.mp4 |
9.61MB |
| 22 - 3 - Evaluating Summaries_ ROUGE.mp4 |
6.53MB |
| 22 - 4 - Summarizing Multiple Documents.mp4 |
13.40MB |
| 2 - 2 - Regular Expressions in Practical NLP (6_04).mp4 |
7.96MB |
| 23 - 1 - Instructor Chat II (5_23).mp4 |
18.63MB |
| 2 - 3 - Word Tokenization (14_26).mp4 |
12.47MB |
| 2 - 4 - Word Normalization and Stemming (11_47).mp4 |
10.08MB |
| 2 - 5 - Sentence Segmentation (5_31).mp4 |
4.97MB |
| 3 - 1 - Defining Minimum Edit Distance (7_04).mp4 |
6.60MB |
| 3 - 2 - Computing Minimum Edit Distance (5_54).mp4 |
5.38MB |
| 3 - 3 - Backtrace for Computing Alignments (5_55).mp4 |
5.53MB |
| 3 - 4 - Weighted Minimum Edit Distance (2_47).mp4 |
2.83MB |
| 3 - 5 - Minimum Edit Distance in Computational Biology (9_29).mp4 |
8.95MB |
| 4 - 1 - Introduction to N-grams (8_41).mp4 |
7.64MB |
| 4 - 2 - Estimating N-gram Probabilities (9_38).mp4 |
9.48MB |
| 4 - 3 - Evaluation and Perplexity (11_09).mp4 |
9.60MB |
| 4 - 4 - Generalization and Zeros (5_15).mp4 |
4.67MB |
| 4 - 5 - Smoothing_ Add-One (6_30).mp4 |
6.04MB |
| 4 - 6 - Interpolation (10_25).mp4 |
9.38MB |
| 4 - 7 - Good-Turing Smoothing (15_35).mp4 |
13.44MB |
| 4 - 8 - Kneser-Ney Smoothing (8_59).mp4 |
8.44MB |
| 5 - 1 - The Spelling Correction Task (5_39).mp4 |
4.84MB |
| 5 - 2 - The Noisy Channel Model of Spelling (19_30).mp4 |
17.79MB |
| 5 - 3 - Real-Word Spelling Correction (9_19).mp4 |
8.56MB |
| 5 - 4 - State of the Art Systems (7_10).mp4 |
6.61MB |
| 6 - 1 - What is Text Classification_ (8_12).mp4 |
7.70MB |
| 6 - 2 - Naive Bayes (3_19).mp4 |
3.25MB |
| 6 - 3 - Formalizing the Naive Bayes Classifier (9_28).mp4 |
8.19MB |
| 6 - 4 - Naive Bayes_ Learning (5_22).mp4 |
6.18MB |
| 6 - 5 - Naive Bayes_ Relationship to Language Modeling (4_35).mp4 |
4.09MB |
| 6 - 6 - Multinomial Naive Bayes_ A Worked Example (8_58).mp4 |
11.38MB |
| 6 - 7 - Precision, Recall, and the F measure (16_16).mp4 |
15.72MB |
| 6 - 8 - Text Classification_ Evaluation (7_17).mp4 |
11.54MB |
| 6 - 9 - Practical Issues in Text Classification (5_56).mp4 |
6.56MB |
| 7 - 1 - What is Sentiment Analysis_ (7_17).mp4 |
9.56MB |
| 7 - 2 - Sentiment Analysis_ A baseline algorithm (13_27).mp4 |
13.18MB |
| 7 - 3 - Sentiment Lexicons (8_37).mp4 |
10.58MB |
| 7 - 4 - Learning Sentiment Lexicons (14_45).mp4 |
18.65MB |
| 7 - 5 - Other Sentiment Tasks (11_01).mp4 |
14.53MB |
| 8 - 1 - Generative vs. Discriminative Models (7_49).mp4 |
7.92MB |
| 8 - 2 - Making features from text for discriminative NLP models (18_11).mp4 |
16.66MB |
| 8 - 3 - Feature-Based Linear Classifiers (13_34).mp4 |
13.46MB |
| 8 - 4 - Building a Maxent Model_ The Nuts and Bolts (8_04).mp4 |
7.80MB |
| 8 - 5 - Generative vs. Discriminative models_ The problem of overcounting evidence (12_15).mp4 |
12.22MB |
| 8 - 6 - Maximizing the Likelihood (10_29).mp4 |
9.83MB |
| 9 - 1 - Introduction to Information Extraction (9_18).mp4 |
9.39MB |
| 9 - 2 - Evaluation of Named Entity Recognition (6_34).mp4 |
6.75MB |
| 9 - 3 - Sequence Models for Named Entity Recognition (15_05).mp4 |
14.15MB |
| 9 - 4 - Maximum Entropy Sequence Models (13_01).mp4 |
13.30MB |