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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 Build smart, AI-driven linguistic applications using deep learning and NLP techniques

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781789802740

Length 276 pages

Edition 1st Edition

Languages

Processing

Tools

Processing

Concepts

Deep Learning

Author (1):

Thomas Dop

View More author details

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 FREE CHAPTER

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

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Summary

In this chapter, we introduced the fundamentals of machine learning and neural networks, as well as a brief overview of transforming text for use within these models. In the next chapter, we will provide a brief overview of PyTorch and how it can be used to construct some of these models.

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Hands-On Natural Language Processing with PyTorch 1.x

Published in: Jul 2020

Publisher: Packt

ISBN-13: 9781789802740

© 2020 Packt Publishing Limited All Rights Reserved

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Authors (1)

Dop

Dop

Thomas Dop is a data scientist at MagicLab, a company that creates leading dating apps, including Bumble and Badoo. He works on a variety of areas within data science, including NLP, deep learning, computer vision, and predictive modeling. He holds an MSc in data science from the University of Amsterdam.

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