Lecture 6: Spelling Correction: Edit Distance

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Lecture 7: Weighted Edit Distance, Other Variations

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Lecture 8: Noisy Channel Model for Spelling Correction

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Lecture 9 : N-Gram Language Models

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Lecture 10: Evaluation of Language Models, Basic Smoothing

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Lecture 11: Tutorial I

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Lecture 12: Language Modeling: Advanced Smoothing Models

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Lecture 13: Computational Morphology

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Lecture 14: Finite - State Methods for Morphology

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Lecture 15: Introduction to POS Tagging

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Lecture 16: Hidden Markov Models for POS Tagging

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Lecture 17: Viterbi Decoding for HMM, Parameter Learning

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Lecture 18: Baum Welch Algorithm

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Lecture 19: Maximum Entropy Models - I

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Lecture 20: Maximum Entropy Models - II

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Lecture 21: Conditional Random Fields

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Lecture 22: Syntax - Introduction

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Lecture 23: Syntax - Parsing I

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Lecture 24: Syntax - CKY, PCFGs

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Lecture 25: PCFGs - Inside-Outside Probabilities

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Lecture 26: Inside-Outside Probabilities

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Lecture 27: Dependency Grammars and Parsing - Introduction

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Lecture 28 : Transition Based Parsing : Formulation

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Lecture 29 : Transition Based Parsing : Learning

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Lecture 30 : MST-Based Dependency Parsing

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Lecture 31: MST-Based Dependency Parsing : Learning

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Lecture 32: Distributional Semantics - Introduction

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Lecture 33: Distributional Models of Semantics

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Lecture 34: Distributional Semantics : Applications, Structured Models

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Lecture 35: Word Embeddings - Part I

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Lecture 36 : Word Embeddings - Part II

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Lecture 37: Lexical Semantics

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Lecture 38: Lexical Semantics - Wordnet

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Lecture 39 : Word Sense Disambiguation - I

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Lecture 40 : Word Sense Disambiguation - II

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Lecture 41 : Novel Word Sense detection

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Lecture 42 : Topic Models : Introduction

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Lecture 43 :Latent Dirichlet Allocation : Formulation

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Lecture 44 : Gibbs Sampling for LDA, Applications

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Lecture 45 : LDA Variants and Applications - I

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Lecture 46:LDA Variants and Applications - II

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Lecture 47 : Entity Linking - I

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Lecture 48 : Entity Linking - II

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Lecture 49 : Information Extraction - Introduction

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Lecture 50 : Relation Extraction

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Lecture 51 : Distant Supervision

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Control structures

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Lecture 52 : Text Summarization - LEXRANK

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Lecture 53 : Optimization based Approaches for Summarization

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Lecture 54 : Summarization Evaluation

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Lecture 55 : Text Classification - I

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Lecture 56 : Text Classification - II

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Lecture 57 : Tutorial II

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Lecture 58 : Tutorial III

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Lecture 59 : Tutorial IV

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Lecture 60 : Tutorial V

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Lecture 61 : Sentiment Analysis - Introduction

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Lecture 62 : Sentiment Analysis - Affective Lexicons

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Lecture 63 : Learning Affective Lexicons

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Lecture 64 : Computing with Affective Lexicons

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Lecture 65 : Aspect - Based Sentiment Analysis

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