© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2021
A. Kulkarni, A. ShivanandaNatural Language Processing Recipeshttps://doi.org/10.1007/978-1-4842-7351-7_3

3. Converting Text to Features

Akshay Kulkarni1   and Adarsha Shivananda1
(1)
Bangalore, Karnataka, India
 
This chapter covers basic to advanced feature engineering (text to features) methods. By the end of the chapter, you will be comfortable with the following recipes.

  • Recipe 1. One-hot encoding

  • Recipe 2. Count vectorizer

  • Recipe 3. n-grams

  • Recipe 4. Co-occurrence matrix

  • Recipe 5. Hash vectorizing

  • Recipe 6. Term frequency-inverse document frequency (TF-IDF)

  • Recipe 7. Word embedding

  • Recipe 8. Implementing fastText

  • Recipe 9. Converting text to features using ...

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