Index of /wp-content/uploads/2017/ST_NLP

[ICO]NameLast modifiedSizeDescription

[PARENTDIR]Parent Directory  -  
[VID]1 - 1 - Course Introduction - Stanford NLP - Professor Dan Jurafsky & Chris Manning-nfoudtpBV68.webm2012-04-01 03:22 17M 
[VID]2 - 1 - Regular Expressions - Stanford NLP - Professor Dan Jurafsky & Chris Manning-hwDhO1GLb_4.webm2012-04-01 04:05 15M 
[VID]2 - 2 - Regular Expressions in Practical NLP - Stanford NLP - Professor Dan Jurafsky & Chris Manning-RGLldper5II.webm2012-04-01 17:20 10M 
[VID]2 - 3 - Word Tokenization- Stanford NLP - Professor Dan Jurafsky & Chris Manning-jBk24DI8kg0.webm2012-04-02 08:30 16M 
[VID]2 - 4 - Word Normalization and Stemming - Stanford NLP - Professor Dan Jurafsky & Chris Manning-2s7f8mBwnko.webm2012-04-02 08:34 13M 
[VID]2 - 5 - Sentence Segmentation - Stanford NLP - Professor Dan Jurafsky & Chris Manning-di0N3kXfGYg.webm2012-04-02 11:27 6.8M 
[VID]3 - 1 - Defining Minimum Edit Distance - Stanford NLP - Professor Dan Jurafsky & Chris Manning-CXfJNzD43OI.webm2012-04-02 11:46 8.7M 
[VID]3 - 2 - Computing Minimum Edit Distance - Stanford NLP - Professor Dan Jurafsky & Chris Manning-z_CB7Gih_Mg.webm2012-04-02 11:55 7.3M 
[VID]3 - 3 - Backtrace for Computing Alignments - Stanford NLP - Professor Dan Jurafsky & Chris Manning-iQVp4Mq6s6k.webm2012-04-02 12:04 7.4M 
[VID]3 - 4 - Weighted Minimum Edit Distance - Stanford NLP - Professor Dan Jurafsky & Chris Manning-ScdU0cHmxfE.webm2012-04-02 12:12 4.0M 
[VID]3-5-Minimum Edit Distance in Computational Biology-Stanford NLP-Dan Jurafsky & Chris Manning-Q0TGn4wkuoE.webm2012-04-02 13:12 12M 
[VID]4 - 1 - Introduction to N-grams- Stanford NLP - Professor Dan Jurafsky & Chris Manning-s3kKlUBa3b0.webm2012-04-02 16:40 11M 
[VID]4 - 2 - Estimating N-gram Probabilities - Stanford NLP - Professor Dan Jurafsky & Chris Manning-o-CvoOkVrnY.webm2012-04-02 17:23 13M 
[VID]4 - 3 - Evaluation and Perplexity - Stanford NLP - Professor Dan Jurafsky & Chris Manning-OHyVNCvnsTo.webm2012-04-02 18:17 13M 
[VID]4 - 4 - Generalization and Zeros - Stanford NLP - Professor Dan Jurafsky & Chris Manning-s5Yg6qac9ag.webm2012-04-03 15:35 6.3M 
[VID]4 - 5 - Smoothing_ Add-One - Stanford NLP - Professor Dan Jurafsky & Chris Manning-d8nVJjlMOYo.webm2012-04-03 16:06 8.4M 
[VID]4 - 6 - Interpolation - Stanford NLP - Professor Dan Jurafsky & Chris Manning--aMYz1tMfPg.webm2012-04-04 04:36 11M 
[VID]4 - 7 - Good-Turing Smoothing - Stanford NLP - Professor Dan Jurafsky & Chris Manning-XdjCCkFUBKU.webm2012-04-04 07:17 16M 
[VID]4 - 8 - Kneser-Ney Smoothing - Stanford NLP - Professor Dan Jurafsky & Chris Manning-wtB00EczoCM.webm2012-04-04 08:33 9.8M 
[VID]5 - 1 - The Spelling Correction Task - Stanford NLP - Professor Dan Jurafsky & Chris Manning-Z1m7McLIP9c.webm2012-04-04 08:50 6.6M 
[VID]5 - 2 - The Noisy Channel Model of Spelling - Stanford NLP - Professor Dan Jurafsky & Chris Manning-RgHr2KVXtiE.webm2012-04-04 09:25 22M 
[VID]5 - 3 - Real-Word Spelling Correction - Stanford NLP - Professor Dan Jurafsky & Chris Manning-AcpGX_fMHEI.webm2012-04-04 09:43 12M 
[VID]5 - 4 - State of the Art Systems - Stanford NLP - Professor Dan Jurafsky & Chris Manning-s7bMicEKmMU.webm2012-04-04 09:59 9.1M 
[VID]6 - 1 - What is Text Classification- Stanford NLP - Professor Dan Jurafsky & Chris Manning-c3fnHA6yLeY.webm2012-04-04 10:04 11M 
[VID]6 - 2 - Naive Bayes - Stanford NLP - Professor Dan Jurafsky & Chris Manning-DdYSMwEWbd4.webm2012-04-04 10:02 4.6M 
[VID]6 - 3 - Formalizing the Naive Bayes Classifier - Stanford NLP-Dan Jurafsky & Chris Manning-TpjPzKODuXo.webm2012-04-04 11:02 11M 
[VID]6 - 4 - Naive Bayes_ Learning - Stanford NLP - Professor Dan Jurafsky & Chris Manning-0hxaqDbdIeE.webm2012-04-04 10:25 8.1M 
[VID]6-5-Naive Bayes_ Relationship to Language Modeling-Stanford NLP-Dan Jurafsky & Chris Manning-ALna9TjBS8Q.webm2012-04-04 10:19 5.5M 
[VID]6 - 6 - Multinomial Naive Bayes_ A Worked Example - Stanford NLP-Dan Jurafsky & Chris Manning-pc36aYTP44o.webm2012-04-04 11:07 13M 
[VID]6 - 7 - Precision, Recall, and the F measure - Stanford NLP - Professor Dan Jurafsky & Chris Manning-2akd6uwtowc.webm2012-04-04 12:27 20M 
[VID]6 - 8 - Text Classification_ Evaluation- Stanford NLP - Professor Dan Jurafsky & Chris Manning-OwwdYHWRB5E.webm2012-04-04 11:12 14M 
[VID]6 - 9 - Practical Issues in Text Classification - Stanford NLP-Dan Jurafsky & Chris Manning-uS58no0_9M4.webm2012-04-04 11:30 8.9M 
[VID]7 - 1 - What is Sentiment Analysis- Stanford NLP - Professor Dan Jurafsky & Chris Manning-sxPBv4Skj98.webm2014-07-02 10:22 10M 
[VID]7 - 2 - Sentiment Analysis_ A baseline algorithm- NLP-Dan Jurafsky & Chris Manning-b9UJ6W0jG1M.webm2012-04-04 12:18 17M 
[VID]7 - 3 - Sentiment Lexicons - Stanford NLP - Professor Dan Jurafsky & Chris Manning-Rv3f1FKzwjM.webm2012-04-04 12:52 13M 
[VID]7 - 4 - Learning Sentiment Lexicons - Stanford NLP - Professor Dan Jurafsky & Chris Manning-_4StZbIYKm8.webm2012-04-04 13:29 23M 
[VID]7 - 5 - Other Sentiment Tasks - Stanford NLP - Professor Dan Jurafsky & Chris Manning-WJP3Pr9PP_8.webm2012-04-04 13:38 18M 
[VID]8 - 1 - Generative vs. Discriminative Models- Stanford NLP - Professor Dan Jurafsky & Chris Manning-qCA1Dk_Ih_c.webm2012-04-04 14:13 11M 
[VID]8 - 2 - Making features from text for discriminative NLP models-Dan Jurafsky & Chris Manning-dype0noxxM0.webm2012-04-04 15:13 22M 
[VID]8 - 3 - Feature-Based Linear Classifiers - Stanford NLP - Professor Dan Jurafsky & Chris Manning-LixC4OJcc9E.webm2012-04-04 17:00 18M 
[VID]8 - 4 - Building a Maxent Model_ The Nuts and Bolts-Dan Jurafsky & Chris Manning-mgBPp2h8qm8.webm2012-04-04 17:29 9.7M 
[VID]8 - 5 - Generative vs. Discriminative models_ The problem of overcounting evidence- Stanford NLP-mzCt4sCTsMU.webm2012-04-04 17:34 15M 
[VID]8 - 6 - Maximizing the Likelihood- Stanford NLP - Professor Dan Jurafsky & Chris Manning-InuXtFCr3WA.webm2012-04-04 17:38 13M 
[VID]9 - 1 - Introduction to Information Extraction- Stanford NLP-Dan Jurafsky & Chris Manning-ZbDts5F8LHg.webm2012-04-04 18:12 12M 
[VID]9 - 2 - Evaluation of Named Entity Recognition- Stanford NLP-Dan Jurafsky & Chris Manning-zUtAtPLrnts.webm2012-04-04 18:16 9.0M 
[VID]9 - 3 - Sequence Models for Named Entity Recognition-NLP-Professor Dan Jurafsky & Chris Manning-mbMrRT5Osbk.webm2012-04-04 19:15 19M 
[VID]9 - 4 - Maximum Entropy Sequence Models- Stanford NLP - Professor Dan Jurafsky & Chris Manning-M1BpelGGeMk.webm2012-04-04 19:31 16M 
[VID]10 - 1 - What is Relation Extraction- Stanford NLP - Professor Dan Jurafsky & Chris Manning-vxdle1YE72I.webm2012-04-05 03:40 13M 
[VID]10 - 2 - Using Patterns to Extract Relations - Stanford NLP - Professor Dan Jurafsky & Chris Manning-VodeEgvxgtA.webm2012-04-05 07:53 7.4M 
[VID]10 - 3 - Supervised Relation Extraction - Stanford NLP - Professor Dan Jurafsky & Chris Manning-Mgz2Ma2NzuM.webm2012-04-05 02:43 13M 
[VID]10 - 4 - Semi-Supervised and Unsupervised Relation Extraction-Dan Jurafsky & Chris Manning-wA-Wvclz8LQ.webm2012-04-05 03:38 13M 
[VID]11 - 1 - The Maximum Entropy Model Presentation-NLP-Dan Jurafsky & Chris Manning-Qn4vZvOEqB0.webm2012-04-13 04:02 16M 
[VID]11 - 2 - Feature Overlap_Feature Interaction-Stanford NLP-Professor Dan Jurafsky & Chris Manning-R-CU72dxwpM.webm2012-04-12 17:54 16M 
[VID]11 - 3 - Conditional Maxent Models for Classification--NLP-Dan Jurafsky & Chris Manning-v-u13mXpCBc.webm2012-04-12 18:42 5.5M 
[VID]11 - 4 - Smoothing_Regularization_Priors for Maxent Models-NLP-Dan Jurafsky & Chris Manning-0tE5185Lbns.webm2012-04-12 21:37 35M 
[VID]12 - 1 - An Intro to Parts of Speech and POS Tagging -NLP-Dan Jurafsky & Chris Manning-LivXkL2DO_w.webm2012-04-13 03:03 15M 
[VID]12 - 2 - Some Methods and Results on Sequence Models for POS Tagging -Dan Jurafsky Chris Manning-RIYQD8zF2e0.webm2012-04-13 04:11 16M 
[VID]13 - 1 - Syntactic Structure_ Constituency vs Dependency -NLP-Dan Jurafsky & Chris Manning-EVgwR9jlIaU.webm2012-04-13 18:39 10M 
[VID]13 - 2 - Empirical_Data-Driven Approach to Parsing-NLP-Dan Jurafsky & Chris Manning-FhReDSvZ35s.webm2012-04-13 16:48 8.3M 
[VID]14 -1-Instructor Chat --NLP-Dan Jurafsky & Chris Manning-F0oDM6usWro.webm2012-04-13 17:23 12M 
[VID]15 - 1 - CFGs and PCFGs -Stanford NLP-Professor Dan Jurafsky & Chris Manning-YQHj4w-sKwQ.webm2012-04-22 06:54 19M 
[VID]15 - 2 - Grammar Transforms-Stanford NLP-Professor Dan Jurafsky & Chris Manning-X22NQirAU_Y.webm2012-04-22 06:49 14M 
[VID]15 - 3 - CKY Parsing -Stanford NLP-Professor Dan Jurafsky & Chris Manning-hq80J8kBg-Y.webm2012-04-22 09:01 31M 
[VID]15 - 4 - CKY Example-Stanford NLP-Professor Dan Jurafsky & Chris Manning-MiEKnFyErbQ.webm2012-04-22 08:44 28M 
[VID]15 - 5 - Constituency Parser Evaluation -Stanford NLP-Professor Dan Jurafsky & Chris Manning-mMXgbrts82M.webm2012-04-22 07:01 12M 
[VID]16 - 1 - Lexicalization of PCFGs-Stanford NLP-Professor Dan Jurafsky & Chris Manning-PLCpYgq2De8.webm2012-04-22 07:16 8.2M 
[VID]16 - 2 - Charniak's Model-Stanford NLP-Professor Dan Jurafsky & Chris Manning-IOOfn5nmtT8.webm2012-04-23 07:41 23M 
[VID]16 - 3 - PCFG Independence Assumptions-Stanford NLP-Professor Dan Jurafsky & Chris Manning-E7U2E1uHsJY.webm2012-04-22 07:53 11M 
[VID]16 - 4 - The Return of Unlexicalized PCFGs-Stanford NLP-Professor Dan Jurafsky & Chris Manning-a9qw0IFjojA.webm2012-04-22 09:32 25M 
[VID]16 - 5 - Latent Variable PCFGs-Stanford NLP-Professor Dan Jurafsky & Chris Manning-xtvP0YbO2Gc.webm2012-04-22 08:41 15M 
[VID]17 - 1 - Dependency Parsing Introduction-Stanford NLP-Professor Dan Jurafsky & Chris Manning-UTnHwzVAIOo.webm2012-04-22 08:30 13M 
[VID]17 - 2 - Greedy Transition-Based Parsing-Stanford NLP-Professor Dan Jurafsky & Chris Manning-ZnW3yet8ngo.webm2012-04-22 09:39 36M 
[VID]17 - 3 - Dependencies Encode Relational Structure-Stanford NLP-Dan Jurafsky & Chris Manning-Lm00hWPmdTQ.webm2012-04-22 08:12 8.3M 
[VID]18 - 1 - Introduction to Information Retrieval-Stanford NLP-Professor Dan Jurafsky & Chris Manning-5L1qemKyUKA.webm2012-04-22 09:12 10M 
[VID]18 - 2 - Term-Document Incidence Matrices -Stanford NLP-Professor Dan Jurafsky & Chris Manning-ftdII-X5SM0.webm2012-04-22 09:18 10M 
[VID]18 - 3 - The Inverted Index-Stanford NLP-Professor Dan Jurafsky & Chris Manning-pevQ2T9Gm0w.webm2012-04-22 09:58 12M 
[VID]18 - 4 - Query Processing with the Inverted Index-Stanford NLP-Dan Jurafsky & Chris Manning-6Md_ZGW-wbk.webm2012-04-22 09:53 7.8M 
[VID]18 - 5 - Phrase Queries and Positional Indexes-Stanford NLP-Professor Dan Jurafsky & Chris Manning-pLeAMnmbh34.webm2012-04-22 11:23 24M 
[VID]19 - 1 - Introducing Ranked Retrieval-Stanford NLP-Professor Dan Jurafsky & Chris Manning-5Gz3Hp217Io.webm2012-04-22 09:36 5.1M 
[VID]19 - 2 - Scoring with the Jaccard Coefficient-Stanford NLP-Professor Dan Jurafsky & Chris Manning-Vbdki_gnnYM.webm2012-04-22 09:46 6.1M 
[VID]19 - 3 - Term Frequency Weighting-Stanford NLP-Professor Dan Jurafsky & Chris Manning-43WvJU4LaUg.webm2012-04-22 09:46 7.2M 
[VID]19 - 4 - Inverse Document Frequency Weighting-Stanford NLP-Professor Dan Jurafsky & Chris Manning-a50Hv_N-yHA.webm2012-04-22 10:04 12M 
[VID]19 - 5 - TF-IDF Weighting-Stanford NLP-Professor Dan Jurafsky & Chris Manning-PhunzHqhKoQ.webm2012-04-22 10:02 4.6M 
[VID]19 - 6 - The Vector Space Model -Stanford NLP-Professor Dan Jurafsky & Chris Manning-ZEkO8QSlynY.webm2012-04-22 12:05 19M 
[VID]19 - 7 - Calculating TF-IDF Cosine Scores-Stanford NLP-Professor Dan Jurafsky & Chris Manning-E3shpvJUZ84.webm2012-04-22 11:41 16M 
[VID]19 - 8 - Evaluating Search Engines -Stanford NLP-Professor Dan Jurafsky & Chris Manning-ds1OKuB7lDw.webm2012-04-22 11:13 10M 
[VID]20 - 1 - Word Senses and Word Relations-NLP-Dan Jurafsky & Chris Manning-T5zOpY_m8xE.webm2012-04-30 03:29 18M 
[VID]20 - 2 - WordNet and Other Online Thesauri -NLP-Dan Jurafsky & Chris Manning-3VEzPbh3qBE.webm2012-04-30 08:41 11M 
[VID]20 - 3 - Word Similarity and Thesaurus Methods -NLP-Dan Jurafsky & Chris Manning-c9zcE1bQhm8.webm2012-04-30 06:09 25M 
[VID]20 - 4 - Word Similarity_ Distributional Similarity I --NLP-Dan Jurafsky & Chris Manning-tYw3gJMumg0.webm2012-04-30 03:44 20M 
[VID]20 - 5 - Word Similarity_ Distributional Similarity II -NLP-Dan Jurafsky & Chris Manning-_JVd0z4R1Ts.webm2012-04-30 03:29 12M 
[VID]21 - 1 - What is Question Answering-NLP-Dan Jurafsky & Chris Manning-DAHZPL6voc4.webm2012-04-30 15:07 11M 
[VID]21 - 2 - Answer Types and Query Formulation-NLP-Dan Jurafsky & Chris Manning-K7VwMBRArgw.webm2012-04-30 14:48 13M 
[VID]21 - 3 - Passage Retrieval and Answer Extraction-NLP-Dan Jurafsky & Chris Manning-cRYf1CT0SpI.webm2012-04-30 15:07 9.8M 
[VID]21 - 4 - Using Knowledge in QA -NLP-Dan Jurafsky & Chris Manning-5io66XP66os.webm2012-04-30 14:48 6.7M 
[VID]21 - 5 - Advanced_ Answering Complex Questions-NLP-Dan Jurafsky & Chris Manning-WRomzf3iwHk.webm2012-04-30 14:57 7.8M 
[VID]22 - 1 - Introduction to Summarization-NLP-Dan Jurafsky & Chris Manning-EZLCOrrl0Wc.webm2012-04-30 15:02 7.2M 
[VID]22 - 2 - Generating Snippets-NLP-Dan Jurafsky & Chris Manning-dOr4NX4Z6-g.webm2012-04-30 15:28 12M 
[VID]22 - 3 - Evaluating Summaries_ ROUGE-NLP-Dan Jurafsky & Chris Manning-IQo5dfMt8Cc.webm2012-04-30 14:46 8.0M 
[VID]22 - 4 - Summarizing Multiple Documents-NLP-Dan Jurafsky & Chris Manning-Vw-7XkP9H1o.webm2012-04-30 17:11 17M 
[VID]23 - 1 - Instructor Chat II -Stanford NLP-Professor Dan Jurafsky & Chris Manning-h5aQV9w-tCI.webm2012-06-08 17:19 11M 

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