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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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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Natural Language Processing 2. Understanding TensorFlow FREE CHAPTER 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

GloVe – Global Vectors representation

Methods for learning word vectors fall into either of two categories: global matrix factorization-based methods or local context window-based methods. Latent Semantic Analysis (LSA) is an example of a global matrix factorization-based method, and skip-gram and CBOW are local context window-based methods. LSA is used as a document analysis technique that maps words in the documents to something known as a concept, a common pattern of words that appears in a document. Global matrix factorization-based methods efficiently exploit the global statistics of a corpus (for example, co-occurrence of words in a global scope), but have shown to perform poorly at word analogy tasks. On the other hand, context window-based methods have been shown to perform well at word analogy tasks, but do not utilize global statistics of the corpus, leaving space for improvement. GloVe attempts to get the best of both worlds—an approach that efficiently leverages...

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