June 2018
Beginner to intermediate
306 pages
7h 42m
English
book
Natural Language Processing and Computational Linguistics
by Brian Sacash, Bhargav Srinivasa-Desikan, Reddy Anil Kumar
Content preview from Natural Language Processing and Computational Linguistics
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Latent Dirichlet allocation
Let's start with the most popular topic modeling algorithm - latent Dirichlet allocation, or LDA as we called it before. The LDA model was created in 2003 by Blei and others and is described in the paper, Latent Dirichlet Allocation [3].
Like we discussed before, LDA helps us model a corpus based on topic distributions, which are in turn made of word distributions. What exactly is a distribution of words? Gensim lets us understand and use this very easily.
Cells 15 and 16 of the Jupyter notebook let you see this.
ldamodel = LdaModel(corpus=corpus, num_topics=10, id2word=dictionary)
That's how easy it is to create a model - just specify the corpus, the dictionary mapping, and the number of topics we want to use ...
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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.
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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.