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Course10610515865 lectures

Natural Language Processing

Prof. Pawan Goyal · IIT Kharagpur

Start with lecture 1 At NPTEL

About

This course starts with the basics of text processing including basic pre-processing, spelling correction, language modeling, Part-of-Speech tagging, Constituency and Dependency Parsing, Lexical Semantics, distributional Semantics and topic models. Finally, the course also covers some of the most interesting applications of text mining such as entity linking, relation extraction, text summarization, text classification, sentiment analysis and opinion mining.

Prerequisites: Basic knowledge of probabilities for the lectures and python for programming assignment

Lectures

Week 1

  1. Lecture 1 : Introduction to the Course YouTube
  2. Lecture 2 : What Do We Do in NLP YouTube
  3. Lecture 3: Why is NLP hard YouTube
  4. Lecture 4: Empirical Laws YouTube
  5. Lecture 5: Text Processing: Basics YouTube

Week 2

  1. Lecture 6: Spelling Correction: Edit Distance YouTube
  2. Lecture 7: Weighted Edit Distance, Other Variations YouTube
  3. Lecture 8: Noisy Channel Model for Spelling Correction YouTube
  4. Lecture 9: N-Gram Language Models YouTube
  5. Lecture 10: Evaluation of Language Models, Basic Smoothing YouTube
  6. Tutorial I YouTube

Week 3

  1. Lecture 11: Language Modeling: Advance Smoothing Models YouTube
  2. Lecture 12: Computational Morphology YouTube
  3. Lecture 13: Finite - State Methods for Morphology YouTube
  4. Lecture 14: Introduction to POS Tagging YouTube
  5. Lecture 15: Hidden Markov Models for POS Tagging YouTube

Week 4

  1. Lecture 16: Viterbi Decoding for HMM, Parameter Learning YouTube
  2. Lecture 17 : Baum Welch Algorithm YouTube
  3. Lecture 18 : Maximum Entropy Models - I YouTube
  4. Lecture 19 : Maximum Entropy Models - II YouTube
  5. Lecture 20: Conditional Random Fields YouTube

Week 5

  1. Lecture 21: Syntax - Introduction YouTube
  2. Lecture 22: Syntax - Parsing I YouTube
  3. Lecture 23: Syntax - CKY, PCFGs YouTube
  4. Lecture 24: PCFGs - Inside-Outside Probabilities YouTube
  5. Lecture 25: Inside-Outside Probabilities YouTube

Week 6

  1. Lecture 26 : Dependency Grammars and Parsing - Introduction YouTube
  2. Lecture 27 : Transition Based Parsing : Formulation YouTube
  3. Lecture 28 : Transition Based Parsing : Learning YouTube
  4. Lecture 29 : MST-Based Dependency Parsing YouTube
  5. Lecture 30 : MST-Based Dependency Parsing : Learning YouTube

Week 7

  1. Lecture 31 : Distributional Semantics - Introduction YouTube
  2. Lecture 32 : Distributional Models of Semantics YouTube
  3. Lecture 33 : Distributional Semantics : Applications, Structured Models YouTube
  4. Lecture 34 : Word Embeddings - Part I YouTube
  5. Lecture 35 : Word Embeddings - Part II YouTube

Week 8

  1. Lecture 36 : Lexical Semantics YouTube
  2. Lecture 37 : Lexical Semantics - Wordnet YouTube
  3. Lecture 38 : Word Sense Disambiguation - I YouTube
  4. Lecture 39 : Word Sense Disambiguation - II YouTube
  5. Lecture 40 : Novel Word Sense detection YouTube

Week 9

  1. Lecture 41 : Topic Models : Introduction YouTube
  2. Lecture 42 : Latent Dirichlet Allocation : Formulation YouTube
  3. Lecture 43 : Gibbs Sampling for LDA, Applications YouTube
  4. Lecture 44 : LDA Variants and Applications - I YouTube
  5. Lecture 45 : LDA Variants and Applications - II YouTube

Week 10

  1. Lecture 46 : Entity Linking - I YouTube
  2. Lecture 47 : Entity Linking - II YouTube
  3. Lecture 48 : Information Extraction - Introduction YouTube
  4. Lecture 49 : Relation Extraction YouTube
  5. Lecture 50 : Distant Supervision YouTube

Week 11

  1. Lecture 51 : Text Summarization - LEXRANK YouTube
  2. Lecture 52 : Optimization Based Approaches for Summarization YouTube
  3. Lecture 53 : Summarization Evaluation YouTube
  4. Lecture 54 : Text Classification - I YouTube
  5. Lecture 55 : Text Classification - II YouTube
  6. Tutorial II YouTube
  7. Tutorial III YouTube
  8. Tutorial IV YouTube
  9. Tutorial V YouTube

Week 12

  1. Lecture 56 : Sentiment Analysis - Introduction YouTube
  2. Lecture 57 : Sentiment Analysis - Affective Lexicons YouTube
  3. Lecture 58 : Learning Affective Lexicons YouTube
  4. Lecture 59 : Computing with Affective Lexicons YouTube
  5. Lecture 60 : Aspect - Based Sentiment Analysis YouTube

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IIT Kharagpur
Department
Computer Science and Engineering
Teacher
Prof. Pawan Goyal
Level
Undergraduate
Language
English
Subjects
Computer science, Engineering
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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