CS 528: Machine Learning Systems Seminar
- CS 528: Machine Learning Systems Seminar
- Spring 2021, Class: Thu 1:30pm-3:00pm
- Location: Online (check Canvas for link) / Sapp Center for Science Teaching and Learning, room 118
- 1 credit, may be repeated
- Instructors: Dan Fu, Karan Goel, Fiodar Kazhamakia, Piero Molino, Matei Zaharia, Chris Ré
- More details (zoom link, attendance form) on Canvas
We’re excited to be offering CS528, a seminar course at Stanford on the frontier of machine learning systems in Fall ‘21 with an all-star cast of invited speakers every week from industry and academia.
Machine learning is driving exciting changes and progress in computing. What does the ubiquity of machine learning mean for how people build and deploy systems and applications? What challenges does industry face when deploying machine learning systems in the real world, and how can academia rise to meet those challenges?
In this seminar series, we’ll take a look at the frontier of machine learning systems, and how machine learning changes the modern programming stack. Our goal is to curate a curriculum of awesome work in ML systems that helps drive research focus to interesting questions.
This class is offered CR/NC only. If you signed up for a letter grade, please change your grading basis on Axess to CR/NC.
- In the first hour of class (Thursdays 1:30-2:30), students are expected to watch the MLSys seminar series live via zoom webinar; see Canvas for the link
- In the last half hour of class (Thursdays 2:30-3:00), students are expected to attend a private class discussion via zoom webinar with an invited guest expert in machine learning systems (often the same guest from the seminar)
- Participate in the private class discussion by asking a minimum of 2 questions
- In addition, students will be asked to write a short (2-3 sentence) reflection every week about the week’s MLSys seminar
Students can miss up to two seminars/discussion sessions per quarter, but they are expected to watch the YouTube recording of the seminar in these cases.
Stanford students can sign up for the class now!