Interpretable Machine Learning: Gaining Practical Insights from Your ML Pipeline

Please join us at Hardy Coffee in Benson for a workshop on Interpretable Machine Learning by Dr. Aimee Schwab-McCoy. First National Bank is our sponsor for the evening, providing coffee and refreshments, beginning at 5:00pm. Please RSVP so we can plan accordingly.

Schedule:
Networking 5:00-5:30pm
Workshop 5:30-6:30pm

How do we extract meaningful information from black box models? Sure, predictive accuracy is important – but what about domain-specific knowledge? Interpretable machine learning, or the use of machine-learning models for the extraction of relevant knowledge about domain relationships (Murdoch et. al, 2018), is a growing area of research in machine learning and statistics. This workshop will introduce the basic principles of interpretable learning and demo some techniques for finding additional insights from machine learning algorithms using RStudio.

Aimee Schwab-McCoy is Assistant Professor of Statistics and Data Science at Creighton University, where she also serves as the Program Director for the Data Science Major and Minor. Dr. Schwab-McCoy completed her PhD in Statistics in 2015, and since then her research has been primarily focused on statistics and data science education. Her work has explored developing quantitative fluency in first-year students, understanding of NHST in biostatistics, attitudes toward statistics instruction across the university. Most recently, Dr. Schwab-McCoy has been studying data science instruction, and the pedagogical strategies employed in data science courses and curricula.