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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

Keras: The model building API of TensorFlow

Keras was developed as a separate library that provides high-level building blocks to build models conveniently. It was initially platform-agnostic and supported many softwares (for example, TensorFlow and Theano).

However, TensorFlow acquired Keras and now is an integral part of TensorFlow for building models effortlessly.

Keras’s primary focus is model building. For that, Keras provides several different APIs with varying degrees of flexibility and complexity. Choosing the right API for the job will require sound knowledge of the limitations of each API as well as experience. The APIs provided by Keras are:

Sequential API – The most easy-to-use API. In this API, you simply stack layers on top of each other to create a model.
Functional API – The functional API provides more flexibility by allowing you to define custom models that can have multiple input layers/multiple output layers.

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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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