CSC/EE 8001: End-to-End ML Systems
Machine learning systems are both complex and unique. Complex because they must balance both performance and accuracy. Unique because they are data-dependent, with data varying widely across use cases. This course covers ML foundations, then dives into data and hypothesis selection, model performance and evaluation, deployment, diagnostics, and MLOps issues in large pipelines. The course is project-based and includes state-of-the-art paper discussions.