Teaching Seminar: James Skripchuk, Introduction to Machine Learning and Classification using K-Nearest Neighbors
Content
Speaker
James Skripchuk (North Carolina State University)
Abstract
What objects are in an image? How can we identify fraudulent credit card charges? Which students are struggling in a class? These complex problems can be tackled by making use of existing data. This short lesson will introduce the basics of how we can write programs that use data to solve problems. While no prior experience in data science or machine learning is required, a basic understanding of programming is recommended.
Bio
James Skripchuk is a Ph.D. candidate and a NSF Graduate Research Fellow at North Carolina State University. His research focuses on how novice programmers navigate and learn to use external information-seeking tools employed by professionals, ranging from Q&A websites to cutting-edge AI code-generation platforms. By understanding how novices use these tools, James aims to design effective pedagogy for “learning how to learn” in the rapidly changing landscape of programming.
Faculty host