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Natural Language Processing with TensorFlow

You're reading from   Natural Language Processing with TensorFlow Teach language to machines using Python's deep learning library

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788478311
Length 472 pages
Edition 1st Edition
Languages
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Authors (2):
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Thushan Ganegedara Thushan Ganegedara
Author Profile Icon Thushan Ganegedara
Thushan Ganegedara
Motaz Saad Motaz Saad
Author Profile Icon Motaz Saad
Motaz Saad
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Understanding TensorFlow 3. Word2vec – Learning Word Embeddings 4. Advanced Word2vec 5. Sentence Classification with Convolutional Neural Networks 6. Recurrent Neural Networks 7. Long Short-Term Memory Networks 8. Applications of LSTM – Generating Text 9. Applications of LSTM – Image Caption Generation 10. Sequence-to-Sequence Learning – Neural Machine Translation 11. Current Trends and the Future of Natural Language Processing A. Mathematical Foundations and Advanced TensorFlow Index

Classical approaches to learning word representation

In this section, we will discuss some of the classical approaches used for numerically representing words. These approaches mainly can be categorized into two classes: approaches that use external resources for representing words and approaches that do not. First, we will discuss WordNet—one of the most popular external resource-based approaches for representing words. Then we will proceed to more localized methods (that is, those that do not rely on external resources), such as one-hot encoding and Term Frequency-Inverse Document Frequency (TF-IDF).

WordNet – using an external lexical knowledge base for learning word representations

WordNet is one of the most popular classical approaches or statistical NLP that deals with word representations. It relies on an external lexical knowledge base that encodes the information about the definition, synonyms, ancestors, descendants, and so forth of a given word. WordNet allows a user...

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