Special Topics in Machine Learning
CDS DS 598
Special Topics in Machine Learning. Please see notes section for current topic.
FALL 2026 Schedule
| Section | Instructor | Location | Schedule | Notes |
|---|---|---|---|---|
| A1 | Saphra | CDS 164 | TR 9:30 am-10:45 am | Fall 2026: Professor Naomi Saphra Course Description: Why do neural networks work? How do they learn? Why do they fail? This course will explore the math and science behind our current understanding of modern machine learning. We will answer where and how these models diverge from both biological models of learning and classical machine learning theory. The outcome of training is determined by decisions about the architecture, training data, and optimizer—as well as random factors with poorly-understood effects. Through paper readings, discussions, and course projects, we will build new intuitions about what to expect from artificial language models (LMs): What is hard for an LM? What is easy for an LM? Why are the hard things hard? And how can we make them easier? Open to CDS Graduate and Undergraduate Students. Undergraduate Pre-reqs: DS122, DS320, DS340 |
FALL 2026 Schedule
| Section | Instructor | Location | Schedule | Notes |
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Note that this information may change at any time. Please visit the MyBU Student Portal for the most up-to-date course information.
