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Sl.No Chapter Name MP4 Download
1Lecture 1: Introduction to the CourseDownload
2Lecture 2: What Do We Do in NLPDownload
3Lecture 3: Why is NLP hardDownload
4Lecture 4: Empirical LawsDownload
5Lecture 5: Text Processing: BasicsDownload
6Lecture 6: Spelling Correction: Edit DistanceDownload
7Lecture 7: Weighted Edit Distance, Other VariationsDownload
8Lecture 8: Noisy Channel Model for Spelling CorrectionDownload
9Lecture 9 : N-Gram Language ModelsDownload
10Lecture 10: Evaluation of Language Models, Basic SmoothingDownload
11Lecture 11: Tutorial IDownload
12Lecture 12: Language Modeling: Advanced Smoothing ModelsDownload
13Lecture 13: Computational MorphologyDownload
14Lecture 14: Finite - State Methods for MorphologyDownload
15Lecture 15: Introduction to POS TaggingDownload
16Lecture 16: Hidden Markov Models for POS TaggingDownload
17Lecture 17: Viterbi Decoding for HMM, Parameter LearningDownload
18Lecture 18: Baum Welch AlgorithmDownload
19Lecture 19: Maximum Entropy Models - IDownload
20Lecture 20: Maximum Entropy Models - IIDownload
21Lecture 21: Conditional Random FieldsDownload
22Lecture 22: Syntax - IntroductionDownload
23Lecture 23: Syntax - Parsing I Download
24Lecture 24: Syntax - CKY, PCFGsDownload
25Lecture 25: PCFGs - Inside-Outside ProbabilitiesDownload
26Lecture 26: Inside-Outside ProbabilitiesDownload
27Lecture 27: Dependency Grammars and Parsing - IntroductionDownload
28Lecture 28 : Transition Based Parsing : FormulationDownload
29Lecture 29 : Transition Based Parsing : LearningDownload
30Lecture 30 : MST-Based Dependency ParsingDownload
31Lecture 31: MST-Based Dependency Parsing : LearningDownload
32Lecture 32: Distributional Semantics - IntroductionDownload
33Lecture 33: Distributional Models of SemanticsDownload
34Lecture 34: Distributional Semantics : Applications, Structured ModelsDownload
35Lecture 35: Word Embeddings - Part IDownload
36Lecture 36 : Word Embeddings - Part IIDownload
37Lecture 37: Lexical SemanticsDownload
38Lecture 38: Lexical Semantics - WordnetDownload
39Lecture 39 : Word Sense Disambiguation - IDownload
40Lecture 40 : Word Sense Disambiguation - IIDownload
41Lecture 41 : Novel Word Sense detectionDownload
42Lecture 42 : Topic Models : IntroductionDownload
43Lecture 43 :Latent Dirichlet Allocation : FormulationDownload
44Lecture 44 : Gibbs Sampling for LDA, Applications Download
45Lecture 45 : LDA Variants and Applications - IDownload
46Lecture 46:LDA Variants and Applications - IIDownload
47Lecture 47 : Entity Linking - IDownload
48Lecture 48 : Entity Linking - IIDownload
49Lecture 49 : Information Extraction - Introduction Download
50Lecture 50 : Relation ExtractionDownload
51Lecture 51 : Distant Supervision Download
52Lecture 52 : Text Summarization - LEXRANKDownload
53Lecture 53 : Optimization based Approaches for SummarizationDownload
54Lecture 54 : Summarization EvaluationDownload
55Lecture 55 : Text Classification - IDownload
56Lecture 56 : Text Classification - IIDownload
57Lecture 57 : Tutorial IIDownload
58Lecture 58 : Tutorial IIIDownload
59Lecture 59 : Tutorial IVDownload
60Lecture 60 : Tutorial VDownload
61Lecture 61 : Sentiment Analysis - IntroductionDownload
62Lecture 62 : Sentiment Analysis - Affective LexiconsDownload
63Lecture 63 : Learning Affective LexiconsDownload
64Lecture 64 : Computing with Affective LexiconsDownload
65Lecture 65 : Aspect - Based Sentiment AnalysisDownload

Sl.No Chapter Name English
1Lecture 1: Introduction to the CourseDownload
Verified
2Lecture 2: What Do We Do in NLPDownload
Verified
3Lecture 3: Why is NLP hardDownload
Verified
4Lecture 4: Empirical LawsDownload
Verified
5Lecture 5: Text Processing: BasicsDownload
Verified
6Lecture 6: Spelling Correction: Edit DistanceDownload
Verified
7Lecture 7: Weighted Edit Distance, Other VariationsDownload
Verified
8Lecture 8: Noisy Channel Model for Spelling CorrectionDownload
Verified
9Lecture 9 : N-Gram Language ModelsDownload
Verified
10Lecture 10: Evaluation of Language Models, Basic SmoothingDownload
Verified
11Lecture 11: Tutorial IDownload
Verified
12Lecture 12: Language Modeling: Advanced Smoothing ModelsDownload
Verified
13Lecture 13: Computational MorphologyDownload
Verified
14Lecture 14: Finite - State Methods for MorphologyDownload
Verified
15Lecture 15: Introduction to POS TaggingDownload
Verified
16Lecture 16: Hidden Markov Models for POS TaggingDownload
Verified
17Lecture 17: Viterbi Decoding for HMM, Parameter LearningDownload
Verified
18Lecture 18: Baum Welch AlgorithmDownload
Verified
19Lecture 19: Maximum Entropy Models - IDownload
Verified
20Lecture 20: Maximum Entropy Models - IIDownload
Verified
21Lecture 21: Conditional Random FieldsDownload
Verified
22Lecture 22: Syntax - IntroductionDownload
Verified
23Lecture 23: Syntax - Parsing I Download
Verified
24Lecture 24: Syntax - CKY, PCFGsDownload
Verified
25Lecture 25: PCFGs - Inside-Outside ProbabilitiesDownload
Verified
26Lecture 26: Inside-Outside ProbabilitiesDownload
Verified
27Lecture 27: Dependency Grammars and Parsing - IntroductionDownload
Verified
28Lecture 28 : Transition Based Parsing : FormulationDownload
Verified
29Lecture 29 : Transition Based Parsing : LearningDownload
Verified
30Lecture 30 : MST-Based Dependency ParsingDownload
Verified
31Lecture 31: MST-Based Dependency Parsing : LearningDownload
Verified
32Lecture 32: Distributional Semantics - IntroductionDownload
Verified
33Lecture 33: Distributional Models of SemanticsDownload
Verified
34Lecture 34: Distributional Semantics : Applications, Structured ModelsDownload
Verified
35Lecture 35: Word Embeddings - Part IDownload
Verified
36Lecture 36 : Word Embeddings - Part IIDownload
Verified
37Lecture 37: Lexical SemanticsDownload
Verified
38Lecture 38: Lexical Semantics - WordnetDownload
Verified
39Lecture 39 : Word Sense Disambiguation - IDownload
Verified
40Lecture 40 : Word Sense Disambiguation - IIDownload
Verified
41Lecture 41 : Novel Word Sense detectionDownload
Verified
42Lecture 42 : Topic Models : IntroductionDownload
Verified
43Lecture 43 :Latent Dirichlet Allocation : FormulationDownload
Verified
44Lecture 44 : Gibbs Sampling for LDA, Applications Download
Verified
45Lecture 45 : LDA Variants and Applications - IDownload
Verified
46Lecture 46:LDA Variants and Applications - IIDownload
Verified
47Lecture 47 : Entity Linking - IDownload
Verified
48Lecture 48 : Entity Linking - IIDownload
Verified
49Lecture 49 : Information Extraction - Introduction Download
Verified
50Lecture 50 : Relation ExtractionDownload
Verified
51Lecture 51 : Distant Supervision Download
Verified
52Lecture 52 : Text Summarization - LEXRANKDownload
Verified
53Lecture 53 : Optimization based Approaches for SummarizationDownload
Verified
54Lecture 54 : Summarization EvaluationDownload
Verified
55Lecture 55 : Text Classification - IDownload
Verified
56Lecture 56 : Text Classification - IIDownload
Verified
57Lecture 57 : Tutorial IIDownload
Verified
58Lecture 58 : Tutorial IIIDownload
Verified
59Lecture 59 : Tutorial IVDownload
Verified
60Lecture 60 : Tutorial VDownload
Verified
61Lecture 61 : Sentiment Analysis - IntroductionDownload
Verified
62Lecture 62 : Sentiment Analysis - Affective LexiconsDownload
Verified
63Lecture 63 : Learning Affective LexiconsDownload
Verified
64Lecture 64 : Computing with Affective LexiconsDownload
Verified
65Lecture 65 : Aspect - Based Sentiment AnalysisDownload
Verified


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2BengaliNot Available
3GujaratiNot Available
4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
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