Unsupervised learning. K-means/medoids. Model-based clustering. Expectation-maximization algorithm. Hierarchical clustering. Dimension reduction. Matrix decomposition. Heatmaps, contour plots, dendograms. Prerequisite: All of DSCI 511, DSCI 521. This course is not eligible for Credit/D/Fail grading.
Unsupervised learning. K-means/medoids. Model-based clustering. Expectation-maximization algorithm. Hierarchical clustering. Dimension reduction. Matrix decomposition. Heatmaps, contour plots, dendograms. Prerequisite: All of DSCI 511, DSCI 521. This course is not eligible for Credit/D/Fail grading.
