Chapter 7: Sentiment Analysis Using AutoKeras

Let's start by defining the unusual term in the title. Sentiment analysis is a term that's widely used in text classification and it is basically about using natural language processing (NLP) in conjunction with machine learning (ML) to interpret and classify emotions in text.

To get an idea of this, let's imagine the task of determining whether a review for a film is positive or negative. You could do this yourself just by reading it, right? However, if our boss sends us a list of 1,000 movie reviews for tomorrow, things become complicated. That's where sentiment analysis becomes an interesting option.

In this chapter, we will use a text classifier to extract sentiments from text data. Most of the concepts of text classification were already explained in Chapter 4, Image Classification and Regression Using AutoKeras, so in this chapter, we will apply them in a practical way by implementing a sentiment predictor...