
NLP analysis of Pride and Prejudice - hribo
https://github.com/cytora/pycon-nlp-in-10-lines/blob/master/01_pride_and_predjudice.ipynb
======
minimaxir
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...](http://www.cytora.com/insights/2016/11/30/natural-language-
processing-in-10-lines-of-code-part-1)

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

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

------
mendelbot
Check out textacy, a higher-level text library built on top of spaCy, for
better keywords extraction:

[https://github.com/chartbeat-labs/textacy](https://github.com/chartbeat-
labs/textacy)

[https://textacy.readthedocs.io/en/latest/api_reference.html#...](https://textacy.readthedocs.io/en/latest/api_reference.html#textacy.keyterms.textrank)

------
Xeoncross
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._)

------
czep
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.

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

Can you share any of your work or give examples?

~~~
czep
This is not my work, but will show you how it's done:
[https://nicschrading.com/project/Intro-to-NLP-with-
spaCy/](https://nicschrading.com/project/Intro-to-NLP-with-spaCy/)

------
wodenokoto
They forgot to run the notebook before uploading the file to github, so there
are no results. What a shame.

Anyway, this is the 2nd part of a 3 part tutorial. Full setup instructions and
the 2 other parts are available here: [https://github.com/cytora/pycon-nlp-
in-10-lines](https://github.com/cytora/pycon-nlp-in-10-lines)

~~~
hribo
Output is not included in the notebook. Hope you still like the tutorial.

~~~
hribo
* Output is NOW included in the notebook

