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Advanced Natural Language Processing with TensorFlow 2

You're reading from   Advanced Natural Language Processing with TensorFlow 2 Build effective real-world NLP applications using NER, RNNs, seq2seq models, Transformers, and more

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781800200937
Length 380 pages
Edition 1st Edition
Languages
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Authors (2):
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Tony Mullen Tony Mullen
Author Profile Icon Tony Mullen
Tony Mullen
Ashish Bansal Ashish Bansal
Author Profile Icon Ashish Bansal
Ashish Bansal
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Toc

Table of Contents (13) Chapters Close

Preface 1. Essentials of NLP 2. Understanding Sentiment in Natural Language with BiLSTMs FREE CHAPTER 3. Named Entity Recognition (NER) with BiLSTMs, CRFs, and Viterbi Decoding 4. Transfer Learning with BERT 5. Generating Text with RNNs and GPT-2 6. Text Summarization with Seq2seq Attention and Transformer Networks 7. Multi-Modal Networks and Image Captioning with ResNets and Transformer Networks 8. Weakly Supervised Learning for Classification with Snorkel 9. Building Conversational AI Applications with Deep Learning 10. Installation and Setup Instructions for Code 11. Other Books You May Enjoy
12. Index

Index

Symbols

VisualEncoder

Transformer model, training with 264

A

abstractive summaries

examples 186, 187

Adaptive Moment Estimation (Adam Optimizer) 119

Attention mechanism 123

Audio-Visual Speech Recognition (AVSR) 228

B

Bahdanau Attention 126

Bahdanau attention layer 197, 198, 199

Batch Normalization (BatchNorm) 245

beam search 171, 180

used, for decoding penalties 218, 219, 220

used for improving text summarization 214, 216, 217

BERT-based transfer learning 123

attention model 125, 127

encoder-decoder networks 123, 124

transformer model 128, 130

BERT fine-tuning approach

for SQuAD question answering 341, 342

bidirectional encoder representations from transformers (BERT) model 132, 133

about 131

custom layers, building 142, 143, 144, 145, 146, 147

normalization 133, 134, 135, 136, 137, 138, 139

sequences 135

tokenization 133, 134, 135, 136, 137, 138, 139

Bi-directional...

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