General information

Course Logistics

• Staff: See the Staff Info page for information about the staff
• Lecture time and place: MWF 9:30 -- 10:20am, CSE2 (Gates) G20

About the Course, Prerequisites and Grading

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 be 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), vector calculus (MATH 126), probability and statistics (CSE 312/STAT390), 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 on 5 homework assignments: HW0 (8%), HW1 (13%), HW2 (13%), HW3 (13%), HW4 (13%). There will be one midterm worth 20% and a final worth another 20%.

Where to get help

• EdStem discussion board:
  • Public/Anonymous Posts
    • Questions like, "Is there a typo in the homework?", "What does this notation mean?", "Is this an accurate description of how this works?".
    • Questions that are not of a personal nature should be posted to the discussion board.
  • Private Posts
    • Questions involving your own code should be posted privately to the EdStem discussion board, not office hours.
    • Personal concerns (like "I was in the hospital", "Laptop was stolen").
• Course staff email cse446-staff@cs.washington.edu (only professors + admin TA):
  • You do not need to email us to use one of the allowable late days, just go ahead and use it.
  • Personal concerns (like "I was in the hospital", "Laptop was stolen") you aren't comfortable sharing with the entire staff. We highly recommend posting privately to EdStem if you are comfortable.
  • Please direct all course-related inquiries to cse446-staff@cs.washington.edu or EdStem. Please do not email the instructors or TAs individually.
• TA office hours:
  • Questions like, "How do I get started on problem 2?", "Am I on the right track?".
  • We will not be able to give detailed code debugging help during office hours. It is too time-consuming for such a large class.
• Professor office hours:
  • General conceptual understanding questions about the class, research or career advice.
  • Questions about the homework are better suited to TA office hours.
• Gradescope should be used for all regrade requests.
• Submit anonymous feedback here.

Frequently Asked Questions

• I still have late days left. Can I use one for this assignment? Yes, and you do not need to email us about it. If you need to go over your 5 allowed late days and you have a reasonable excuse, you can email cse446-staff@cs.washington.edu to ask about it.
• I want to register but the class is full. Can I get an add code? Add codes are given out according to a centralized process organized by CSE. You can reach out to ugrad-adviser@cs.washington.edu or check out the following resources:
  • https://www.cs.washington.edu/academics/ugrad/advising/
  • https://www.cs.washington.edu/academics/ugrad/courses/petition
  • https://www.cs.washington.edu/students/ugrad/non-major-registration
• What is the formula for curving the courses? Will it be posted? No. Curving each course will be based on an affine transformation of scores up to the discretion of the instructors alone and will not be publicly posted.