Books & Videos

Table of Contents

  1. Chapter 1 Language Processing and Python

    1. Computing with Language: Texts and Words

    2. A Closer Look at Python: Texts as Lists of Words

    3. Computing with Language: Simple Statistics

    4. Back to Python: Making Decisions and Taking Control

    5. Automatic Natural Language Understanding

    6. Summary

    7. Further Reading

    8. Exercises

  2. Chapter 2 Accessing Text Corpora and Lexical Resources

    1. Accessing Text Corpora

    2. Conditional Frequency Distributions

    3. More Python: Reusing Code

    4. Lexical Resources

    5. WordNet

    6. Summary

    7. Further Reading

    8. Exercises

  3. Chapter 3 Processing Raw Text

    1. Accessing Text from the Web and from Disk

    2. Strings: Text Processing at the Lowest Level

    3. Text Processing with Unicode

    4. Regular Expressions for Detecting Word Patterns

    5. Useful Applications of Regular Expressions

    6. Normalizing Text

    7. Regular Expressions for Tokenizing Text

    8. Segmentation

    9. Formatting: From Lists to Strings

    10. Summary

    11. Further Reading

    12. Exercises

  4. Chapter 4 Writing Structured Programs

    1. Back to the Basics

    2. Sequences

    3. Questions of Style

    4. Functions: The Foundation of Structured Programming

    5. Doing More with Functions

    6. Program Development

    7. Algorithm Design

    8. A Sample of Python Libraries

    9. Summary

    10. Further Reading

    11. Exercises

  5. Chapter 5 Categorizing and Tagging Words

    1. Using a Tagger

    2. Tagged Corpora

    3. Mapping Words to Properties Using Python Dictionaries

    4. Automatic Tagging

    5. N-Gram Tagging

    6. Transformation-Based Tagging

    7. How to Determine the Category of a Word

    8. Summary

    9. Further Reading

    10. Exercises

  6. Chapter 6 Learning to Classify Text

    1. Supervised Classification

    2. Further Examples of Supervised Classification

    3. Evaluation

    4. Decision Trees

    5. Naive Bayes Classifiers

    6. Maximum Entropy Classifiers

    7. Modeling Linguistic Patterns

    8. Summary

    9. Further Reading

    10. Exercises

  7. Chapter 7 Extracting Information from Text

    1. Information Extraction

    2. Chunking

    3. Developing and Evaluating Chunkers

    4. Recursion in Linguistic Structure

    5. Named Entity Recognition

    6. Relation Extraction

    7. Summary

    8. Further Reading

    9. Exercises

  8. Chapter 8 Analyzing Sentence Structure

    1. Some Grammatical Dilemmas

    2. What’s the Use of Syntax?

    3. Context-Free Grammar

    4. Parsing with Context-Free Grammar

    5. Dependencies and Dependency Grammar

    6. Grammar Development

    7. Summary

    8. Further Reading

    9. Exercises

  9. Chapter 9 Building Feature-Based Grammars

    1. Grammatical Features

    2. Processing Feature Structures

    3. Extending a Feature-Based Grammar

    4. Summary

    5. Further Reading

    6. Exercises

  10. Chapter 10 Analyzing the Meaning of Sentences

    1. Natural Language Understanding

    2. Propositional Logic

    3. First-Order Logic

    4. The Semantics of English Sentences

    5. Discourse Semantics

    6. Summary

    7. Further Reading

    8. Exercises

  11. Chapter 11 Managing Linguistic Data

    1. Corpus Structure: A Case Study

    2. The Life Cycle of a Corpus

    3. Acquiring Data

    4. Working with XML

    5. Working with Toolbox Data

    6. Describing Language Resources Using OLAC Metadata

    7. Summary

    8. Further Reading

    9. Exercises

  1. Appendix Afterword: The Language Challenge

    1. Language Processing Versus Symbol Processing

    2. Contemporary Philosophical Divides

    3. NLTK Roadmap

    4. Envoi...

  2. Appendix Bibliography

  3. NLTK Index

  4. General Index

  5. Colophon