Let's now apply these feature transformers and feature extractors to a very modern real-world use case—sentiment analysis. In sentiment analysis, the goal is to classify the underlying human sentiment—for example, whether the writer is positive, neutral, or negative towards the subject of a text. To many organizations, sentiment analysis is an important technique that is used to better understand their customers and target markets. For example, sentiment analysis can be used by retailers to gauge the public's reaction to a particular product, or by politicians to assess public mood towards a policy or news item. In our case study, we will examine tweets about airlines in order to predict whether customers are saying positive or negative things about them. Our analysis could then be used by airlines in order to improve...
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