NPTEL : NOC:Natural Language Processing (Computer Science and Engineering)

Co-ordinators : Prof. Pawan Goyal


Lecture 1 - Introduction to the Course

Lecture 2 - What Do We Do in NLP

Lecture 3 - Why is NLP hard

Lecture 4 - Empirical Laws

Lecture 5 - Text Processing: Basics

Lecture 6 - Spelling Correction: Edit Distance

Lecture 7 - Weighted Edit Distance, Other Variations

Lecture 8 - Noisy Channel Model for Spelling Correction

Lecture 9 - N-Gram Language Models

Lecture 10 - Evaluation of Language Models, Basic Smoothing

Lecture 11 - Tutorial I

Lecture 12 - Language Modeling: Advanced Smoothing Models

Lecture 13 - Computational Morphology

Lecture 14 - Finite - State Methods for Morphology

Lecture 15 - Introduction to POS Tagging

Lecture 16 - Hidden Markov Models for POS Tagging

Lecture 17 - Viterbi Decoding for HMM, Parameter Learning

Lecture 18 - Baum Welch Algorithm

Lecture 19 - Maximum Entropy Models - I

Lecture 20 - Maximum Entropy Models - II

Lecture 21 - Conditional Random Fields

Lecture 22 - Syntax - Introduction

Lecture 23 - Syntax - Parsing I

Lecture 24 - Syntax - CKY, PCFGs

Lecture 25 - PCFGs - Inside-Outside Probabilities

Lecture 26 - Inside-Outside Probabilities

Lecture 27 - Dependency Grammars and Parsing - Introduction

Lecture 28 - Transition Based Parsing : Formulation

Lecture 29 - Transition Based Parsing : Learning

Lecture 30 - MST-Based Dependency Parsing

Lecture 31 - MST-Based Dependency Parsing : Learning

Lecture 32 - Distributional Semantics - Introduction

Lecture 33 - Distributional Models of Semantics

Lecture 34 - Distributional Semantics : Applications, Structured Models

Lecture 35 - Word Embeddings - Part I

Lecture 36 - Word Embeddings - Part II

Lecture 37 - Lexical Semantics

Lecture 38 - Lexical Semantics - Wordnet

Lecture 39 - Word Sense Disambiguation - I

Lecture 40 - Word Sense Disambiguation - II

Lecture 41 - Novel Word Sense detection

Lecture 42 - Topic Models : Introduction

Lecture 43 - Latent Dirichlet Allocation : Formulation

Lecture 44 - Gibbs Sampling for LDA, Applications

Lecture 45 - LDA Variants and Applications - I

Lecture 46 - LDA Variants and Applications - II

Lecture 47 - Entity Linking - I

Lecture 48 - Entity Linking - II

Lecture 49 - Information Extraction - Introduction

Lecture 50 - Relation Extraction

Lecture 51 - Distant Supervision

Lecture 52 - Text Summarization - LEXRANK

Lecture 53 - Optimization based Approaches for Summarization

Lecture 54 - Summarization Evaluation

Lecture 55 - Text Classification - I

Lecture 56 - Text Classification - II

Lecture 57 - Tutorial II

Lecture 58 - Tutorial III

Lecture 59 - Tutorial IV

Lecture 60 - Tutorial V

Lecture 61 - Sentiment Analysis - Introduction

Lecture 62 - Sentiment Analysis - Affective Lexicons

Lecture 63 - Learning Affective Lexicons

Lecture 64 - Computing with Affective Lexicons

Lecture 65 - Aspect - Based Sentiment Analysis