Learning about Machine Learning: An Introduction
Presented at SPSP 2021 Annual Convention
Machine learning algorithms accommodate big data of the sort that traditional statistics cannot. This session introduces attendees to broadly applicable principles of machine learning: e.g., bias vs. variance tradeoffs, robust prediction and clustering, and quantitative vs. text-oriented analyses. R code and sample APA write-up will be provided to equip and inspire those attending.
Speakers: Fred Oswald, Rice University