© Dipanjan Sarkar 2019
Dipanjan SarkarText Analytics with Pythonhttps://doi.org/10.1007/978-1-4842-4354-1_4

4. Feature Engineering for Text Representation

Dipanjan Sarkar1 
(1)
Bangalore, Karnataka, India
 

In the previous chapters, we saw how to understand, process, and wrangle text data. However, all machine learning or deep learning models are limited because they cannot understand text data directly and they only understand numeric representations of features as inputs. In this chapter, we look at how to work with text data, which is definitely one of the most abundant sources of unstructured data. Text data usually consists of documents that can represent words, sentences, or even paragraphs of free-flowing text. The inherent lack of structure ...

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