| Instructor: | Jamie Morgenstern |
| Lecture: | Thursday, 6:30–9:20 PM — CSE2 G10 |
| Discussion: | Ed (edstem.org) — all non-personal questions should be posted here. |
| Staff email: | csep546-staff@cs.washington.edu |
| Anonymous feedback: | feedback.cs.washington.edu |
Machine learning explores the study and construction of algorithms that can learn from historical data and make inferences about future outcomes. This study is a marriage of algorithms, computation, and statistics, so this class will have healthy doses of each. The goals of this course are to provide a thorough grounding in the fundamental methodologies and algorithms of machine learning.
Prerequisites: Students entering the class should be comfortable with programming and should have a pre-existing working knowledge of linear algebra (MATH 308 or equivalent), vector calculus (MATH 126 or equivalent), probability and statistics (CSE 312/STAT 390 or equivalent), and algorithms. For a brief refresher, consult the reference materials on the Textbooks page.
Grading: Your grade will be based exclusively on 5 homework assignments: HW0 (10%), HW1 (20%), HW2 (20%), HW3 (20%), HW4 (30%). There are no exams. Curving will be based on an affine transformation of scores at the instructor’s discretion and will not be publicly posted.
We take academic integrity very seriously. Please read the UW Student Conduct Code: Academic Misconduct. If you’re uncertain about whether something is academic misconduct, ask the Instructor or TAs at least 24 hours before the assignment is due.
This course welcomes all students of all backgrounds. You should expect and demand to be treated by your classmates and the course staff with respect. If any incident occurs that challenges this commitment to a supportive, diverse, inclusive, and equitable environment, please let the instructor know so the issue can be addressed.
University policy prohibits all forms of sexual harassment. If you feel you have been a victim of sexual harassment or discrimination, you may speak with your instructor, the department chair, or file a complaint with the UW Ombudsman’s Office (339 HUB, 206-543-6028) or the University Complaint Investigation and Resolution Office (UCIRO) (22 Gerberding Hall).
Your access in this course is important to us. If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to us at your earliest convenience. If you have a temporary health condition or permanent disability that requires accommodations, please contact DRS at 206-543-8924, uwdrs@uw.edu, or disability.uw.edu.