NLP Class Videos | 719A9FEA7EA5E1DEC8797B2C5614415A7D49A1DA

NLP Class Videos

Name	NLP Class Videos	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.2 GB
Total Files	120
Hash	719A9FEA7EA5E1DEC8797B2C5614415A7D49A1DA

/
1 - 1 - Course Introduction (14:11).mp4	12.9 MB
/1. Basic Text Processing/
2 - 1 - Regular Expressions (11:25).mp4	11.4 MB
2 - 2 - Regular Expressions in Practical NLP (6:04).mp4	8.4 MB
2 - 3 - Word Tokenization (14:26).mp4	13.1 MB
2 - 4 - Word Normalization and Stemming (11:47).mp4	10.6 MB
2 - 5 - Sentence Segmentation (5:31).mp4	5.2 MB
/10. Parsing Intro/
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
13 - 3 - The Exponential Problem in Parsing (14:30).mp4	15.6 MB
/11. Probablistic Parsing/
15 - 1 - CFGs and PCFGs (15:29).mp4	17.5 MB
15 - 2 - Grammar Transforms (12:05).mp4	12.6 MB
15 - 3 - CKY Parsing (23:25).mp4	27.5 MB
15 - 4 - CKY Example (21:52).mp4	24.6 MB
15 - 5 - Constituency Parser Evaluation (9:45).mp4	11.2 MB
/12. Lexicalized Parsing/
16 - 1 - Lexicalization of PCFGs (7:03).mp4	7.5 MB
16 - 2 - Charniak's Model (18:23).mp4	19.9 MB
16 - 3 - PCFG Independence Assumptions (9:44).mp4	10.3 MB
16 - 4 - The Return of Unlexicalized PCFGs (20:53).mp4	22.2 MB
16 - 5 - Latent Variable PCFGs (12:07).mp4	13.2 MB
/13. Dependency Parsing (Optional)/
17 - 1 - Dependency Parsing Introduction (10:25).mp4	11.7 MB
17 - 2 - Greedy Transition-Based Parsing (31:05).mp4	32.9 MB
17 - 3 - Dependencies Encode Relational Structure (7:20).mp4	7.6 MB
/14. Information Retrieval/
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 - 3 - The Inverted Index (10:42).mp4	11.2 MB
18 - 4 - Query Processing with the Inverted Index (6:43).mp4	7.1 MB
18 - 5 - Phrase Queries and Positional Indexes (19:45).mp4	21.6 MB
/15. Ranked Information Retrieval/
19 - 1 - Introducing Ranked Retrieval (4:27).mp4	4.8 MB
19 - 2 - Scoring with the Jaccard Coefficient (5:06).mp4	5.7 MB
19 - 3 - Term Frequency Weighting (5:59).mp4	6.7 MB
19 - 4 - Inverse Document Frequency Weighting (10:16).mp4	11.7 MB
19 - 5 - TF-IDF Weighting (3:42).mp4	4.3 MB
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 - 8 - Evaluating Search Engines (9:02).mp4	9.2 MB
/16. Semantics/
20 - 1 - Word Senses and Word Relations (11:50).mp4	15.6 MB
20 - 2 - WordNet and Other Online Thesauri (6:23).mp4	9.2 MB
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 - 5 - Word Similarity: Distributional Similarity II (8:15).mp4	9.9 MB
/17. Sentiment Analysis/
7 - 1 - What is Sentiment Analysis? (7:17).mp4	10.0 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 - 4 - Learning Sentiment Lexicons (14:45).mp4	19.6 MB
7 - 5 - Other Sentiment Tasks (11:01).mp4	15.2 MB
/18. Question Answering/
21 - 1 - What is Question Answering? (7:28).mp4	9.3 MB
21 - 2 - Answer Types and Query Formulation (8:47).mp4	10.6 MB
21 - 3 - Passage Retrieval and Answer Extraction (6:38).mp4	8.1 MB
21 - 4 - Using Knowledge in QA (4:25).mp4	5.5 MB
21 - 5 - Advanced: Answering Complex Questions (4:52).mp4	6.5 MB
/19. Summarization/
22 - 1 - Introduction to Summarization.mp4	6.3 MB
22 - 2 - Generating Snippets.mp4	10.1 MB
22 - 3 - Evaluating Summaries: ROUGE.mp4	6.8 MB
22 - 4 - Summarizing Multiple Documents.mp4	14.1 MB
/2. Edit Distance/
3 - 1 - Defining Minimum Edit Distance (7:04).mp4	6.9 MB
3 - 2 - Computing Minimum Edit Distance (5:54).mp4	5.6 MB
3 - 3 - Backtrace for Computing Alignments (5:55).mp4	5.8 MB
3 - 4 - Weighted Minimum Edit Distance (2:47).mp4	3.0 MB
3 - 5 - Minimum Edit Distance in Computational Biology (9:29).mp4	9.4 MB
/3. Language Modelling/
4 - 1 - Introduction to N-grams (8:41).mp4	8.0 MB
4 - 2 - Estimating N-gram Probabilities (9:38).mp4	9.9 MB
4 - 3 - Evaluation and Perplexity (11:09).mp4	10.1 MB
4 - 4 - Generalization and Zeros (5:15).mp4	4.9 MB
4 - 5 - Smoothing: Add-One (6:30).mp4	6.3 MB
4 - 6 - Interpolation (10:25).mp4	9.8 MB
4 - 7 - Good-Turing Smoothing (15:35).mp4	14.1 MB
4 - 8 - Kneser-Ney Smoothing (8:59).mp4	8.8 MB
/4. Spelling Correction/
5 - 1 - The Spelling Correction Task (5:39).mp4	5.1 MB
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. Text Classification/
6 - 1 - What is Text Classification? (8:12).mp4	8.1 MB
6 - 2 - Naive Bayes (3:19).mp4	3.4 MB
6 - 3 - Formalizing the Naive Bayes Classifier (9:28).mp4	8.6 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 - 6 - Multinomial Naive Bayes: A Worked Example (8:58).mp4	11.9 MB
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 - 9 - Practical Issues in Text Classification (5:56).mp4	6.9 MB
/6. Discriminative Classifiers: Max Entropy Classifiers/
8 - 1 - Generative vs. Discriminative Models (7:49).mp4	8.3 MB
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 - 4 - Building a Maxent Model: The Nuts and Bolts (8:04).mp4	8.2 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
/7. Named entity recognition and Maximum Entropy Sequence Models/
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
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
/8. Relation Extraction/
10 - 1 - What is Relation Extraction? (9:47).mp4	10.7 MB
10 - 2 - Using Patterns to Extract Relations (6:17).mp4	6.4 MB
10 - 3 - Supervised Relation Extraction (10:51).mp4	10.8 MB
10 - 4 - Semi-Supervised and Unsupervised Relation Extraction (9:53).mp4	10.6 MB
/9. Advanced Entropy Max Models/
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
11 - 4 - Smoothing_Regularization_Priors for Maxent Models (29:24).mp4	30.2 MB
/9. POS Tagging/
12 - 1 - An Intro to Parts of Speech and POS Tagging (13:19).mp4	12.5 MB
12 - 2 - Some Methods and Results on Sequence Models for POS Tagging (13:04).mp4	13.4 MB
/Lecture Slides/
0.pdf	2.8 MB
1.pdf	896.4 KB
10.pdf	911.3 KB
11.pdf	1.2 MB
12.pdf	1.5 MB
13.pdf	900.2 KB
14.pdf	2.5 MB
15.pdf	2.3 MB
16.pdf	2.5 MB
17.pdf	1.9 MB
18.pdf	1.6 MB
19.pdf	1.5 MB
2.pdf	1.3 MB
3.pdf	2.2 MB
4.pdf	1.5 MB
5.pdf	1.8 MB
6.pdf	1.9 MB
7.pdf	1.0 MB
8.pdf	1.6 MB
9.pdf	717.0 KB
Total files 120