TITLE: Artificial Intelligence for Medicine & Health
INSTRUCTOR: Professor Mark Chang, Boston University
MODERATOR: Wenjin Wang
Text data is increasingly important in many domains of applied statistics, and tidy data principles and tidy tools can make text mining easier and more effective. In this workshop, Dr. Silge will demonstrate how we can manipulate, summarize, and visualize the characteristics of text using these methods and R packages from the tidy tool ecosystem. These tools are highly effective for many analytical questions and allow analysts to integrate natural language processing into effective workflows already in wide use. We will explore how to implement approaches such as sentiment analysis of texts, measuring tf-idf, finding word vectors, and modeling using text features.