March 2019
Intermediate to advanced
640 pages
23h 40m
English
Objectives
In this chapter you’ll:
Perform natural language processing (NLP) tasks, which are fundamental to many of the forthcoming data science case study chapters.
Run lots of NLP demos.
Use the TextBlob, NLTK, Textatistic and spaCy NLP libraries and their pretrained models to perform various NLP tasks.
Tokenize text into words and sentences.
Use parts-of-speech tagging.
Use sentiment analysis to determine whether text is positive, negative or neutral.
Detect the language of text and translate between languages using TextBlob’s Google Translate support.
Get word roots via stemming and lemmatization.
Use TextBlob’s spell checking and correction capabilities.
Get word definitions, synonyms and antonyms. ...
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