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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

Product type Paperback

Published in May 2018

Publisher Packt

ISBN-13 9781788478311

Length 472 pages

Edition 1st Edition

Languages

Processing

Tools

Processing

Concepts

Deep Learning

Authors (2):

Thushan Ganegedara

Motaz Saad

View More author details

Table of Contents (14) Chapters

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

Evaluating text results output from the RNN

Here we will display a segment of text we generated using our RNN. We will show results of when we do not use input unrolling as well as when we use input unrolling.

Without input unrolling, we get the following after 10 epochs:

    he the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the
    o the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the the t

With input unrolling, we get the following after 10 epochs:

... god grant that our sister may be here, and then we shall be free.  when the maiden,who was standing behind the door watching, heard that wish,
she came forth...

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Authors (2)

Ganegedara

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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Saad

Saad

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