There’s so much information stored in text – how can we make sense of it all? How can a machine deal with the complexities of English, or translate between languages? Can a machine learn analogies: New York is to USA as London is to where? In this talk we’ll explore and demo text analysis with word2vec, using some simple R code. We’ll answer all these questions, show some real life case studies and more.
Required audience experience
Intro level, no experience required. Some R code will be demonstrated, so a little familiarity with R would help, but is not essential.
Objective of the talk
To demonstrate the power of text analytic techniques for making sense of text. To introduce the word2vec word embedding algorithm, and how it can be used in R. To explore its capacity for encoding meaning, word association, finding synonyms, and performing mathematical operations with text.