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/STAT390 or equivalent), and algorithms. For a brief refresher, we recommend that you consult the linear algebra and statistics/probability 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 or credit given in any way other than the homeworks (e.g., no credit given for attending lecture or section). Curving will be based on an affine transformation of the scores up to the discretion of the instructor and will not be publicly posted.
We take academic integrity very seriously. Behaving with integrity is part of our responsibility to our shared learning community. Please read the UW Student Conduct Code: Academic Misconduct for more information. If you're uncertain about if something is academic misconduct, please ask the Instructor or TAs. We are happy to discuss any questions you may have.
This course welcomes all students of all backgrounds. The computer science and computer engineering industries have significant lack of diversity. This is due to a lack of sufficient past efforts by the field toward even greater diversity, equity, and inclusion. The Allen School seeks to create a more diverse, inclusive, and equitable environment for our community and our field. 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 if you feel you have been discriminated against, you may speak with your instructor, teaching assistant, the chair of the department, or you can file a complaint with the UW Ombudsman's Office for Sexual Harassment. Their office is located at 339 HUB, (206) 543-6028. There is a second office, the University Complaint Investigation and Resolution Office (UCIRO), who also investigate complaints. The UCIRO is located at 22 Gerberding Hall. Please see additional resources at: http://www.washington.edu/about/ombudsman/role.html and http://f2.washington.edu/treasury/riskmgmt/UCIRO.
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 so we can coordinate your arrangements. 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. DRS offers resources and coordinates reasonable accommodations for students with disabilities.
Last updated: Winter 2026