** This session is open to both C15 and C16 fellows **
PREWORK: None
SESSION DESCRIPTION:Clustering is a fundamental component of data science’s machine learning toolbox. This session will explore the foundational concepts of clustering, and, through practical examples, provide insights into how it may be useful for analyzing education-related data. As part of this session, an R-based Jupyter notebook will be provided to participants as a reference if they wish to implement k-means clustering in their work.What is clustering?
- In which situations would clustering be helpful/appropriate?
- How do you conduct a clustering analysis and interpret the results?
- Use some examples from ETSU’s work to walk through the process
SESSION MATERIALS:
