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

Product type Paperback

Published in Jul 2022

Publisher Packt

ISBN-13 9781838641351

Length 514 pages

Edition 2nd Edition

Languages

Processing

Tools

Processing

Concepts

Machine Learning

Author (1):

Thushan Ganegedara

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Table of Contents (15) Chapters

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

Evaluating the results quantitatively

There are many different techniques for evaluating the quality and the relevancy of the captions generated. We will briefly discuss several such metrics we can use to evaluate the captions. We will discuss four metrics: BLEU, ROGUE, METEOR, and CIDEr.

All these measures share a key objective, to measure the adequacy (the meaning of the generated text) and fluency (the grammatical correctness of text) of the generated text. To calculate all these measures, we will use a candidate sentence and a reference sentence, where a candidate sentence is the sentence/phrase predicted by our algorithm and the reference sentence is the true sentence/phrase we want to compare with.

BLEU

Bilingual Evaluation Understudy (BLEU) was proposed by Papineni and others in BLEU: A Method for Automatic Evaluation of Machine Translation, Proceedings of the 40^th Annual Meeting of the Association for Computational Linguistics (ACL), Philadelphia, July (2002)...

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

Table of Contents (15) Chapters

Evaluating the results quantitatively

BLEU

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Authors (1)