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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

MS-COCO dataset for image captioning

Microsoft published the Common Objects in Context or COCO dataset in 2014. All the versions of the dataset can be found at cocodataset.org. The COCO dataset is a big dataset that's used for object detection, segmentation, and captioning, among other annotations. Our focus will be on the 2014 training and validation images, where five captions per image are available. There are roughly 83K images in the training set and 41K images in the validation set. The training and validation images and captions need to be downloaded from the COCO website.

Large download warning: The training image dataset is approximately 13 GB, while the validation dataset is over 6 GB. The annotations for the image files, which include captions, are about 214 MB in size. Please be careful of your internet bandwidth usage and potential costs as you download this dataset.

Google has also published a new Conceptual Captions dataset at https://ai.google...

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