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Computer Science & IT

Natural Language Processing

Natural Language Processing

01 Introduction

02 Stages of NLP

03 Stages of NLP Continue

04 Two approaches to NLP

05 Sequence Labelling and Noisy Channel

06 Argmax Based Computation

07 Argmax Based Computation

08 Noisy Channel Application to NLP

09 Brief on Probabilistic Parsing & Start of Part of Speech Tagging

10 Part of Speech Tagging

11 Part of Speech Tagging counted

12 Part of Speech Tagging counted & Indian Language in Focus; Morphology Analysis

13 PoS Tagging contd� , Indian Language Consideration; Accuracy Measure

14 PoS Tagging; Fundamental Principle; Why Challenging; accuracy

15 PoS Tagging; Accuracy Measurement; Word categories

16 AI and Probability; HMM

18 HMM, Viterbi, Forward Backward Algorithm

19 HMM, Viterbi, Forward Backward Algorithm Contd..

20 HMM, Forward Backward Algorithms, Baum Welch Algorithm

21 HMM, Forward Backward Algorithms, Baum Welch Algorithm Contd...

22 Natural Language Processing and Informational Retrieval

23 CLIA; IR Basics

24 IR Models Boolean Vector

25 IR Models NLP and IR Relationship

26 NLP and IR How NLP has used IR, Toward Latent Semantic

27 Least Square Method Recap of PCA Towards Latent Semantic Indexing(LSI)

28 PCA; SVD; Towards Latent Semantic Indexing(LSI)

29 Wordnet and Word Sense Disambiguation

30 Wordnet and Word Sense Disambiguation(contd�)

31 Wordnet; Metonymy and Word Sense Disambiguation

32 Word Sense Disambiguation

33 Word Sense Disambiguation; Overlap Based Method; Supervised Method

34 Word Sense Disambiguation Supervised and Unsupervised methods

35 Word Sense Disambiguation Semi - Supervised and Unsupervised method resource - constrained WSD

36 Resource Constrained WSD; Parsing

38 Parsing Algorithm

39 Parsing Ambiguous Sentences; Probabilistic Parsing

40 Probabilistic Parsing Algorithms

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