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Natural Language Processing with TensorFlow

You're reading from   Natural Language Processing with TensorFlow The definitive NLP book to implement the most sought-after machine learning models and tasks

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781838641351
Length 514 pages
Edition 2nd Edition
Languages
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Author (1):
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Thushan Ganegedara Thushan Ganegedara
Author Profile Icon Thushan Ganegedara
Thushan Ganegedara
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Toc

Table of Contents (15) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 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

Index

Symbols

1-gram precision 354

A

Adam optimizer 13

additive attention layer

reference link 344

Amazon Web Services (AWS)

URL 21

Anaconda

download link 18

installation link 18

installing 18

Application Programming Interface (API) 24

attention patterns

visualizing 355, 357, 360

AutoGraph 26

Automatic Language Processing Advisory Committee (ALPAC) 314

average pooling 157

B

backpropagation (BP) 197

avoiding, for RNNs 199

working 197, 198

Backpropagation Through Time (BPTT) 197, 256

limitations 201, 202

RNNs, training 200

bag-of-words 6, 8

batch normalization 376

Bayes' rule 461, 462

beam 260

beam length 260

beam search 260, 301, 302

implementing 302, 304

text, generating with 304, 305

used, for improving LSTMs 260, 261

bell curve 459

Bidirectional Encoder Representation from Transformers (BERT) 377, 378

answering questions, with 399,...

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