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Deep Learning with TensorFlow and Keras – 3rd edition

You're reading from   Deep Learning with TensorFlow and Keras – 3rd edition Build and deploy supervised, unsupervised, deep, and reinforcement learning models

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Product type Paperback
Published in Oct 2022
Publisher Packt
ISBN-13 9781803232911
Length 698 pages
Edition 3rd Edition
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Authors (3):
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Sujit Pal Sujit Pal
Author Profile Icon Sujit Pal
Sujit Pal
Antonio Gulli Antonio Gulli
Author Profile Icon Antonio Gulli
Antonio Gulli
Dr. Amita Kapoor Dr. Amita Kapoor
Author Profile Icon Dr. Amita Kapoor
Dr. Amita Kapoor
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Table of Contents (23) Chapters Close

Preface 1. Neural Network Foundations with TF 2. Regression and Classification FREE CHAPTER 3. Convolutional Neural Networks 4. Word Embeddings 5. Recurrent Neural Networks 6. Transformers 7. Unsupervised Learning 8. Autoencoders 9. Generative Models 10. Self-Supervised Learning 11. Reinforcement Learning 12. Probabilistic TensorFlow 13. An Introduction to AutoML 14. The Math Behind Deep Learning 15. Tensor Processing Unit 16. Other Useful Deep Learning Libraries 17. Graph Neural Networks 18. Machine Learning Best Practices 19. TensorFlow 2 Ecosystem 20. Advanced Convolutional Neural Networks 21. Other Books You May Enjoy
22. Index

Text documents

What do text and images have in common? At first glance, very little. However, if we represent a sentence or a document as a matrix, then this matrix is not much different from an image matrix where each cell is a pixel. So, the next question is, how can we represent a piece of text as a matrix?

Well, it is pretty simple: each row of a matrix is a vector that represents a basic unit for the text. Of course, now we need to define what a basic unit is. A simple choice could be to say that the basic unit is a character. Another choice would be to say that a basic unit is a word; yet another choice is to aggregate similar words together and then denote each aggregation (sometimes called cluster or embedding) with a representative symbol.

Note that regardless of the specific choice adopted for our basic units, we need to have a 1:1 mapping from basic units into integer IDs so that the text can be seen as a matrix. For instance, if we have a document with 10 lines...

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