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Real-world Natural Language Processing shows you how to build the practical NLP applications that are transforming the way humans and computers work together. Guided by clear explanations of each core NLP topic, you’ll create many interesting applications including a sentiment analyzer and a chatbot. Along the way, you’ll use Python and open source libraries like AllenNLP and HuggingFace Transformers to speed up your development process.
Table of Contents
- Real-World Natural Language Processing
- inside front cover
- Copyright
- dedication
- contents
- front matter
- Part 1 Basics
- 1 Introduction to natural language processing
- 2 Your first NLP application
- 3 Word and document embeddings
- 4 Sentence classification
- 5 Sequential labeling and language modeling
- Part 2 Advanced models
- 6 Sequence-to-sequence models
- 7 Convolutional neural networks
- 8 Attention and Transformer
- 9 Transfer learning with pretrained language models
- Part 3 Putting into production
- 10 Best practices in developing NLP applications
- 11 Deploying and serving NLP applications
- index