Text Analysis with R, Part II
This three-part series will take a deeper dive into text analysis and natural language processing tasks using R. In this second session, we will examine and implement a set of "unsupervised" approaches to understanding text, including co-occurrence, clustering, and topic models. Prerequisites: basic experience using R and familiarity with text processing at the level of part I in this series.
Instructor: Michele Claibourn
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