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Natural Language Processing with NLTK and Gensim

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Speakers: Tony Ojeda, Benjamin Bengfort, Laura Lorenz

In this tutorial, we will begin by exploring the features of the NLTK library. We will then focus on building a language-aware data product - a topic identification and document clustering algorithm from a web crawl of blog sites. The clustering algorithm will use a simple Lesk K-Means clustering to start, and then will improve with an LDA analysis using the popular Gensim library.

Slides can be found at: https://speakerdeck.com/pycon2016 and https://github.com/PyCon/2016-slides

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