Course Information
Over the past few years, machine learning has become an important technique to successfully solve problems in many different fields, such as vision, NLP, robotics. An important ingredient that is driving this success is the development of machine learning systems that efficiently support the task of learning and inference of complicated models using many devices and possibly using distributed resources. The study of how to build and optimize these machine learning systems is now an active area of research and commercialization. This is a special topics seminar course that covers various aspects of machine learning systems. We will meet twice every week. We will have two classes per week. The class will either be a lecture or discussion session. Each class will study a specific aspect of machine learning systems.
Students are required to read some of the selected papers and present at one of the discussion sessions. Students will form teams to work on a final project in the area of machine learning systems. The course should be appropriate for graduate students in all areas who are interested in the topic of machine learning and systems.
- Lectures: Tuesday/Thursday 10:40am - noon, the Zoom Link and recordings available in Canvas
- Office Hours: Check the time below, the Zoom Link available in Piazza
- Announcement or Discussion: Piazza
- Submitting your work: Gradescope
- Contact: please make a private post in Piazza
- Instructor Tianqi Chen
- Office hours: upon request
- TA Byungsoo Jeon
- Office hours: Friday, 4:00-5:00 pm (+ upon request)
- TA Tian Li
- Office hours: Friday, 2:30-3:30 pm (+ upon request)
