The Fall 2019 offering of the graduate-level course NPB/NSC 287A “topics in theoretical neurocience” is focusing on Statistical Learning Theory. Data analysis techniques at the boundary of statistics and computer science have become necessary tools for revealing structure in complex data sets. This quarter, learn the foundations of statistical learning theory as we focus on core principles and methods from the classic text An Introduction to Statistical Learning (with Applications in R).

Topics will include:
– Linear & nonlinear regression approaches
– Cross-validation & bootstrapping
– Model selection and regularization techniques
– Classification & clustering methods

Credit: 2 units.
CRN: 52784 (for NPB 287A); 52945 (for NSC 287A)

For course questions, email instructor Mark Goldman.