November 2016
Beginner to intermediate
687 pages
15h 31m
English
book
Natural Language Processing: Python and NLTK
by Nitin Hardeniya, Jacob Perkins, Deepti Chopra, Nisheeth Joshi, Iti Mathur
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Summary
In this chapter, we touched upon some of the most popular social networks. You learned how to get data using Python. You understood the structure and kind of attributes data has. We explored different options provided by the API.
We explored some of the most common use cases in the context of social media mining. We touched upon the use cases about trending topics, influencer detection, information flow, and so on. We visualized some of these use cases. We also applied some of the learnings from the previous chapter, where we used NLTK to get some of the topic and entity extraction, while in scikit-learn we classified some of the complaints.
In conclusion, I would suggest that you look for some of the same use cases in context of some other ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.