July 2017
Beginner to intermediate
486 pages
13h 49m
English
Content preview from Python Natural Language Processing
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Vectorization
Vectorization is an important aspect of feature extraction in the NLP domain. Transforming the text into a vector format is a major task.
Vectorization techniques try to map every possible word to a specific integer. There are many available APIs that make your life easier. scikit-learn has DictVectorizer to convert text to a one-hot encoding form. The other API is the CountVectorizer, which converts the collection of text documents to a matrix of token counts. Last but not least, there are a couple of other APIs out there. We can also use word2vec to convert text data to the vector form. Refer to this link's From text section for more details:
http://scikit-learn.org/stable/modules/classes.html#module-sklearn.feature_extraction.text ...
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