DSCC 265
Introduction to Statistical Machine Learning
The course provides an introduction to modern machine learning concepts, techniques, and algorithms. Topics discussed include regression, clustering and classification, kernels, support vector machines, feature selection, goodness of fit, neural networks. Programming assignments emphasize taking theory into practice, through applications on real-world data sets. Students will be expected to work with Python programming environment to complete the assignments.
Sources
- Course catalogue ↗2026-2027
Catalogue variants
- Introduction to Statistical Machine Learning · 4.0