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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

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Deep Learning with TensorFlow 2 and Keras - Second Edition Antonio Gulli Amita Kapoor Sujit Pal

ISBN: 978-1-83882-341-2

  • Build machine learning and deep learning systems with TensorFlow 2 and the Keras API
  • Use Regression analysis, the most popular approach to machine learning
  • Understand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiers
  • Use GANs (generative adversarial networks) to create new data that fits with existing patterns
  • Discover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret another
  • Apply deep learning to natural human language and interpret natural language texts to produce an appropriate response
  • Train your models on the cloud and put TF to work...
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