Essential Natural Language Processing
A friendly introduction using Python
Ekaterina Kochmar
  • MEAP began October 2019
  • Publication in Summer 2020 (estimated)
  • ISBN 9781617296765
  • 325 pages (estimated)
  • printed in black & white

Great content, tone, presentation, figures, and code. Pedagogical and thorough—friendly and engaging.

Erik Hansson
Essential Natural Language Processing gives you everything you need to get started with NLP in a friendly, understandable tutorial. Full of Python code and hands-on projects, each chapter provides a concrete example with practical techniques that you can put into practice right away. If you’re a beginner to NLP and want to upgrade your applications with functions and features like information extraction, user profiling, and automatic topic labeling, this is the book for you.
Table of Contents detailed table of contents

Part 1: First steps

1 Introduction

1.1 A brief history of NLP

1.2 Typical tasks

1.2.2 Advanced Information Search: Asking the machine precise questions

1.2.3 Conversational agents and Intelligent virtual assistants

1.2.4 Text prediction and Language generation

1.2.5 Spam filtering

1.2.6 Machine translation

1.2.7 Spell- and grammar checking

1.3 Summary

2 Your first NLP example

2.1 Introducing NLP in practice: spam filtering

2.2 Understanding the task

2.3 Implementing your own spam filter

2.3.1 Step 1: Define the data and classes

2.3.2 Step 2: Split the text into words

2.3.3 Step 3: Extract and normalize the features

2.3.4 Step 4: Train the classifier

2.3.5 Step 5: Evaluate your classifier

2.4 Deploying your spam filter in practice

2.5 Summary

Part 2: Practical NLP

3 Introduction to Information Search

3.1 Understanding the task

3.1.1 Data and data structures

3.1.2 Boolean search algorithm

3.2 Processing the data further

3.2.1 Preselecting the words that matter: stopwords removal

3.2.2 Matching forms of same word: morphological processing

3.3 Information weighing

3.3.1 Weighing words with term frequency

3.3.2 Weighing words with inverse document frequency

3.4 Practical use of the search algorithm

3.4.1 Retrieval of the most similar documents

3.4.2 Evaluation of the results

3.4.3 Deploying search algorithm in practice

3.5 Summary

4 Information Extraction

5 User Profiling

6 Sentiment Analysis

7 Named Entity Recognition

8 Topic Labeling

9 Summarization

Part 3: Next steps

10 Further guidance for an NLP practitioner

Appendixes: Reference guide to the essential building blocks

Appendix A: NLP essentials: core terminology

Appendix B: Machine Learning cheat sheet

Appendix C: Your essential toolset

About the Technology

Natural Language Processing is a set of data science techniques that enable machines to make sense of human text and speech. Advances in machine learning and deep learning have made NLP more efficient and reliable than ever, leading to a huge number of new tools and resources. From improving search applications to sentiment analysis, the possible applications of NLP are vast and growing.

About the book

Essential Natural Language Processing is a hands-on guide to NLP with practical techniques you can put into action right away. By following the numerous Python-based examples and real-world case studies, you’ll apply NLP to search applications, extracting meaning from text, sentiment analysis, user profiling, and more. When you’re done, you’ll have a solid grounding in NLP that will serve as a foundation for further learning.

What's inside

  • Extracting information from raw text
  • Named entity recognition
  • Automating summarization of key facts
  • Topic labeling

About the reader

For beginners to NLP with basic Python skills.

About the author

Ekaterina Kochmar is an Affiliated Lecturer and a Senior Research Associate at the Natural Language and Information Processing group of the Department of Computer Science and Technology, University of Cambridge. She holds an MA degree in Computational Linguistics, an MPhil in Advanced Computer Science, and a PhD in Natural Language Processing.

Manning Early Access Program (MEAP) Read chapters as they are written, get the finished eBook as soon as it’s ready, and receive the pBook long before it's in bookstores.
MEAP combo $39.99 pBook + eBook + liveBook
MEAP eBook $31.99 pdf + ePub + kindle + liveBook
Prices displayed in rupees will be charged in USD when you check out.

placing your order...

Don't refresh or navigate away from the page.

FREE domestic shipping on three or more pBooks