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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

Product type Paperback

Published in Mar 2019

Publisher

ISBN-13 9781789954043

Length 374 pages

Edition 1st Edition

Languages

Processing

Tools

NLTK

Concepts

Mobile Application Development

Authors (2):

Dwight Gunning

Sohom Ghosh

View More author details

Table of Contents (10) Chapters

Preface

About the Book

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

7. Vector Representation

Learning Objectives

By the end of this chapter, you will be able to:

Describe the need for vector representation in Natural Language Processing (NLP)
Identify the various ways that text can be represented as vectors
Describe word vectors and their various forms
Implement vector arithmetic
Describe document vectors

In this chapter, you will be learning about various encoding techniques using which a text can be represented as vector.

The rest of the chapter is locked

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Authors (2)

Sohom Ghosh

Sohom Ghosh

Sohom Ghosh is a passionate data detective with expertise in natural language processing. He has worked extensively in the data science arena with a specialization in deep learning-based text analytics, NLP, and recommendation systems. He has publications in several international conferences and journals.

See other products by Sohom Ghosh

Dwight Gunning

Dwight Gunning

Dwight Gunning is a data scientist at FINRA, a financial services regulator in the US. He has extensive experience in Python-based machine learning and hands-on experience with the most popular NLP tools such as NLTK, gensim, and spacy.

See other products by Dwight Gunning

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