Natural Language Processing aggregates several tasks that can be performed, like:
- Part of speech tagging
- Word segmentation
- Named entity recognition
- Machine translation
- Question answering
- Sentiment analysis
- Topic segmentation and recognition
- Natural language generation
It all starts though with preparing text for further processing. In this lab you will learn how to use some of the NLTK capabilities to clean and prepare text data.
Introduction to NLTK
To start working with Python use the following command:
In this scenario we will be working with the NLTK library. In some way we will repeat some work from the previous scenario using the library instead of vanilla Python.
Let's read movie reviews again.
documents = data_reader.read_reviews()
Then we can look as an example document (feel free to change the index and load different document).
example_idx = 123
document = documents[example_idx]