© Taweh Beysolow II 2018
Taweh Beysolow IIApplied Natural Language Processing with Python https://doi.org/10.1007/978-1-4842-3733-5_4

4. Topic Modeling and Word Embeddings

Taweh Beysolow II1 
(1)
San Francisco, California, USA
 

Now that you have had an introduction to working with text data, let’s dive into one of the more advanced feature extraction algorithms. To accomplish some of the more difficult problems, it is reasonable for me to introduce you to other techniques to approach NLP problems. We will move through Word2Vec, Doc2Vec, and GloVe.

Topic Model and Latent Dirichlet Allocation (LDA)

Topic models are a method of extracting information from bodies of text to see what “topics” occur across all the documents. The intuition is that we expect ...

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