Feature engineering is the most important part of developing NLP applications. Features are the input parameters for machine learning (ML) algorithms. These ML algorithms generate output based on the input features. Feature engineering is a kind of art and skill because it generates the best possible features, and choosing the best algorithm to develop NLP application requires a lot of effort and understanding about feature engineering as well as NLP and ML algorithms. In Chapter 2, Practical Understanding of Corpus and Dataset, we saw how data is gathered and what the different formats of data or corpus are. In Chapter 3, Understanding Structure of Sentences, we touched on some of the basic but important aspects of NLP and linguistics. We will use these concepts to derive features in this chapter. In Chapter 4, Preprocessing, we looked preprocessing...
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