EE 660 Machine Learning II: Mathematical Foundations and Methods

Units: 4
Terms Offered: Fa

Supervised, semi-supervised, and unsupervised machine learning; domain adaptation and transfer learning; human interpretability. Feasibility of learning, model complexity, and performance (error) on unseen data.
Prerequisite: EE 503 and EE 510 and EE 559
Recommended Preparation: Experience with Python at the level of EE 541. Familiarity with general machine learning methods including regression and classification and with computational complexity at the level of EE 538
Instruction Mode: Lecture, Discussion
Grading Option: Letter