Search icon
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

You're reading from  Deep Learning with TensorFlow and Keras – 3rd edition - Third Edition

Product type Book
Published in Oct 2022
Publisher Packt
ISBN-13 9781803232911
Pages 698 pages
Edition 3rd Edition
Languages
Authors (3):
Amita Kapoor Amita Kapoor
Profile icon Amita Kapoor
Antonio Gulli Antonio Gulli
Profile icon Antonio Gulli
Sujit Pal Sujit Pal
Profile icon Sujit Pal
View More author details

Table of Contents (23) Chapters

Preface 1. Neural Network Foundations with TF 2. Regression and Classification 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...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €14.99/month. Cancel anytime}