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Natural Language Processing Fundamentals

You're reading from   Natural Language Processing Fundamentals Build intelligent applications that can interpret the human language to deliver impactful results

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Product type Paperback
Published in Mar 2019
Publisher
ISBN-13 9781789954043
Length 374 pages
Edition 1st Edition
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Authors (2):
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Dwight Gunning Dwight Gunning
Author Profile Icon Dwight Gunning
Dwight Gunning
Sohom Ghosh Sohom Ghosh
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Sohom Ghosh
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Basic Feature Extraction Methods 3. Developing a Text classifier 4. Collecting Text Data from the Web 5. Topic Modeling 6. Text Summarization and Text Generation 7. Vector Representation 8. Sentiment Analysis Appendix

Vector Definition

There are various mathematical representations, such as scalars, vectors, matrices, and tensors. A scalar can be considered as a number, a decimal, or even a fraction. A matrix can be considered as a rectangular array of numbers. A vector is a collection of numbers that represent some real objects. You can think of a vector as a row in a matrix. A tensor is a general concept that can be comprised of scalars, vectors, and matrices.

The following diagram shows how scalars, vectors, matrices, and tensors are different from each other:

Figure 7.1: Scalars, vectors, matrices, and tensors
Figure 7.1: Scalars, vectors, matrices, and tensors

Now, try to think about text as follows::

  • A letter that is a single unit of an alphabet
  • A word that is a series of letters
  • A sentence that is a series or words
  • A paragraph that is a sequence of words
  • A document that is a collection of words, possibly broken down into paragraphs

Each of the preceding units are in text format...

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