Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Python Natural Language Processing

You're reading from   Hands-On Python Natural Language Processing Explore tools and techniques to analyze and process text with a view to building real-world NLP applications

Arrow left icon
Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838989590
Length 316 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Mayank Rasu Mayank Rasu
Author Profile Icon Mayank Rasu
Mayank Rasu
Aman Kedia Aman Kedia
Author Profile Icon Aman Kedia
Aman Kedia
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Introduction
2. Understanding the Basics of NLP FREE CHAPTER 3. NLP Using Python 4. Section 2: Natural Language Representation and Mathematics
5. Building Your NLP Vocabulary 6. Transforming Text into Data Structures 7. Word Embeddings and Distance Measurements for Text 8. Exploring Sentence-, Document-, and Character-Level Embeddings 9. Section 3: NLP and Learning
10. Identifying Patterns in Text Using Machine Learning 11. From Human Neurons to Artificial Neurons for Understanding Text 12. Applying Convolutions to Text 13. Capturing Temporal Relationships in Text 14. State of the Art in NLP 15. Other Books You May Enjoy

Understanding vectors and matrices

The introduction to this chapter touched upon the challenge of representing text data in a mathematical form. Two of the most popular data structures used with text data are vectors and matrices. We will now have a look at each one of these in detail.

Vectors

Vectors are a one-dimensional array of numbers in which each number could be identified by its respective indices. They are typically represented as a column enclosed in square brackets, as shown here:

In this example, the x vector has three elements, and these three elements store information about the vector. Mathematicians abstract vectors as an object in space, where each element of the vector represents the projection of that vector along a given axis. We often use the term Rn to define a vector, where R is a representation mechanism and n denotes the number of dimensions used to describe the vector. In general, Rn is the set of all n-tuples of real numbers.

In the preceding example, the...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime