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NLP analysis of Pride and Prejudice

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Re: NLP analysis of Pride and Prejudice

#3
Spacy is a great library and tutorials like this give a clear and simple path for testing it out. They even included a function for reading a file, rather than assuming the audience are all python programers.

(Not that reading a file is hard, but it's an extra few minutes as you google how to read a file in X language.)

Re: NLP analysis of Pride and Prejudice

#4

Hmm, why isn't the cell output included? Additionally, Jupyter Notebooks on GitHub do not render; instead, you should visit the site of the original post: http://www.cytora.com/insights/2016/11/30/natural-language-p...

They do if you don't strip the results before publishing, which seems to be what happened here.

Re: NLP analysis of Pride and Prejudice

#7

Hmm, why isn't the cell output included? Additionally, Jupyter Notebooks on GitHub do not render; instead, you should visit the site of the original post: http://www.cytora.com/insights/2016/11/30/natural-language-p...

They do if you don't strip the results before publishing, which seems to be what happened here.

From reading the commands, the cells were never even executed.

Re: NLP analysis of Pride and Prejudice

#8
Spacy is awesome. The API is clean and powerful. I have been using it heavily over the past few months, using it almost exclusively for feature extraction now. I'm currently working on extracting subject-verb-object tuples, which is amazingly easy to do, because I am finding these to be much more powerful than unigrams or ngrams for classification.

Named Entity extraction in Spacy is another killer feature. It's been instrumental in some fraud detection work I've been doing as well.

Re: NLP analysis of Pride and Prejudice

#9
post #8

Spacy is awesome. The API is clean and powerful. I have been using it heavily over the past few months, using it almost exclusively for feature extraction now. I'm currently working on extracting subject-verb-object tuples, which is amazingly easy to do, because I am finding these to be much more powerful than unigrams or ngrams for classification. Named Entity extraction in Spacy is another killer feature. It's been…

> working on extracting subject-verb-object tuples, which is amazingly easy to do

Can you share any of your work or give examples?

Re: NLP analysis of Pride and Prejudice

#10

Hmm, why isn't the cell output included? Additionally, Jupyter Notebooks on GitHub do not render; instead, you should visit the site of the original post: http://www.cytora.com/insights/2016/11/30/natural-language-p...

Cell output is now included in repository. Thanks for the feedback.
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