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Hands-On Natural Language Processing with PyTorch 1.x

You're reading from  Hands-On Natural Language Processing with PyTorch 1.x

Product type Book
Published in Jul 2020
Publisher Packt
ISBN-13 9781789802740
Pages 276 pages
Edition 1st Edition
Languages
Author (1):
Thomas Dop Thomas Dop
Profile icon Thomas Dop

Table of Contents (14) Chapters

Preface 1. Section 1: Essentials of PyTorch 1.x for NLP
2. Chapter 1: Fundamentals of Machine Learning and Deep Learning 3. Chapter 2: Getting Started with PyTorch 1.x for NLP 4. Section 2: Fundamentals of Natural Language Processing
5. Chapter 3: NLP and Text Embeddings 6. Chapter 4: Text Preprocessing, Stemming, and Lemmatization 7. Section 3: Real-World NLP Applications Using PyTorch 1.x
8. Chapter 5: Recurrent Neural Networks and Sentiment Analysis 9. Chapter 6: Convolutional Neural Networks for Text Classification 10. Chapter 7: Text Translation Using Sequence-to-Sequence Neural Networks 11. Chapter 8: Building a Chatbot Using Attention-Based Neural Networks 12. Chapter 9: The Road Ahead 13. Other Books You May Enjoy

Future NLP tasks

While the majority of this book has been focused on text classification and sequence generation, there are a number of other NLP tasks that we haven't really touched on. While many of these are more interesting from an academic perspective rather than a practical perspective, it's important to understand these tasks as they form the basis of how language is constructed and formed. Anything we, as NLP data scientists, can do to better understand the formation of natural language will only improve our understanding of the subject matter. In this section, we will discuss, in more detail, four key areas of future development in NLP:

  • Constituency parsing
  • Semantic role labeling
  • Textual entailment
  • Machine comprehension

Constituency parsing

Constituency parsing (also known as syntactic parsing) is the act of identifying parts of a sentence and assigning a syntactic structure to it. This syntactic structure is largely determined by the...

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