Real-World Natural Language Processing

2 Your first NLP application

This chapter covers

• Building a sentiment analyzer using AllenNLP
• Applying basic machine learning concepts (datasets, classification, and regression)
• Employing neural network concepts (word embeddings, recurrent neural networks, linear layers)
• Training the model through reducing loss
• Evaluating and deploying your model

In section 1.1.2, we saw how not to do NLP. In this chapter, we are going to discuss how to do NLP in a more principled, modern way. Specifically, we’d like to build a sentiment analyzer using a neural network. Even though the sentiment analyzer we are going to build is a simple application and the library (AllenNLP) takes care of most heavy lifting, it is a full-fledged NLP application that covers ...