Text Mining with R
If you work in analytics or data science you are familiar with the fact that data is being generated all the time at ever-faster rates. Analysts are often trained to handle tabular or rectangular data that are mostly numeric, but much of the data proliferating today is unstructured and text-heavy. Many of us who work in analytical fields are not trained in even the simplest approaches to analyzing unstructured text data. This short course serves as an introduction to text mining with the R programming language.
Upon successfully completing this course, students will be able to use R to:
- Assess regular expressions within unstructured text.
- Tidy unstructured text data.
- Perform word frequency analysis.
- Quantify the sentiment in text.
- Assess the frequency and importance of terms across documents.
- Understand the relationship between words.
- Perform topic modeling analysis.
Course fee: $750, includes breakfasts, lunches, refreshments, and free parking for both days.
U-Square. Room 359
225 Calhoun Street
Cincinnati, OH 45219 (Google Maps link)
Brad Boehmke, Ph.D, is the Director of Data Science at 84.51°, professor at three universities, author of the Data Wrangling with R book, and creator of multiple R open source packages and data science short courses. He focuses on developing algorithmic processes, solutions, and tools that enable 84.51° and its analysts to efficiently extract insights from data and provide solution alternatives to decision-makers. He has a wide analytic skill set covering descriptive, predictive, and prescriptive analytic capabilities applied across multiple domains including retail, healthcare, cyber intelligence, finance, Department of Defense, and aerospace. Summary of his works is available online.