November 2018
Beginner to intermediate
182 pages
4h 48m
English
Content preview from Natural Language Processing with Python Quick Start Guide
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spaCy for tokenization
spaCy loads the English model using the preceding .load syntax. This tells spaCy what rules, logic, weights, and other information to use:
%%time import spacy # python -m spacy download en # uncomment above line to download the model nlp = spacy.load('en')
While we use only 'en' or English examples in this book, spaCy supports these features for more languages. I have used their multi-language tokenizer for Hindi as well, and have been satisfied with the same:
The %%time syntax measures the CPU and Wall time at your runtime execution for the cell in a Jupyter not ebook.
doc = nlp(text)
This creates a spaCy object, doc. The object stores pre-computed linguistic features, including tokens. Some NLP libraries, especially ...
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