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Natural Language Processing with TensorFlow - Second Edition

You're reading from Natural Language Processing with TensorFlow - Second Edition

Product type Book

Published in Jul 2022

Publisher Packt

ISBN-13 9781838641351

Pages 514 pages

Edition 2nd Edition

Languages

Concepts

Mobile Application Development

Author (1):

Thushan Ganegedara

Table of Contents (15) Chapters

Preface

1. Introduction to Natural Language Processing

2. Understanding TensorFlow 2

3. Word2vec – Learning Word Embeddings

4. Advanced Word Vector Algorithms

5. Sentence Classification with Convolutional Neural Networks

6. Recurrent Neural Networks

7. Understanding Long Short-Term Memory Networks

8. Applications of LSTM – Generating Text

9. Sequence-to-Sequence Learning – Neural Machine Translation

10. Transformers

11. Image Captioning with Transformers

12. Other Books You May Enjoy

13. Index

Appendix A: Mathematical Foundations and Advanced TensorFlow

Preparing data for the NMT system

In this section, we will understand the data and learn about the process for preparing data for training and predicting from the NMT system. First, we will talk about how to prepare training data (that is, the source sentence and target sentence pairs) to train the NMT system, followed by inputting a given source sentence to produce the translation of the source sentence.

The dataset

The dataset we’ll be using for this chapter is the WMT-14 English-German translation data from https://nlp.stanford.edu/projects/nmt/. There are ~4.5 million sentence pairs available. However, we will use only 250,000 sentence pairs due to computational feasibility. The vocabulary consists of the 50,000 most common English words and the 50,000 most common German words, and words not found in the vocabulary will be replaced with a special token, <unk>. You will need to download the following files:

train.de – File containing German...

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Authors (1)

Thushan Ganegedara

Thushan is a seasoned ML practitioner with 4+ years of experience in the industry. Currently he is a senior machine learning engineer at Canva; an Australian startup that founded the online visual design software, Canva, serving millions of customers. His efforts are particularly concentrated in the search and recommendations group working on both visual and textual content. Prior to Canva, Thushan was a senior data scientist at QBE Insurance; an Australian Insurance company. Thushan was developing ML solutions for use-cases related to insurance claims. He also led efforts in developing a Speech2Text pipeline there. He obtained his PhD specializing in machine learning from the University of Sydney in 2018.

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