Machine Learning Systems Seminar

Download as PDF

Course Description

Machine learning is driving exciting changes and progress in computing systems. 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 new system designs meet those challenges? In this weekly talk series, we will invite speakers working at the frontier of machine learning systems, and focus on how machine learning changes the modern programming stack. Topics will include programming models for ML, infrastructure to support ML applications such as ML Platforms, debugging, parallel computing, and hardware for ML. May be repeated for credit.

Grading Basis

RSN - Satisfactory/No Credit

Min

1

Max

1

Course Repeatable for Degree Credit?

No

Course Component

Seminar

Enrollment Optional?

No

Does this course satisfy the University Language Requirement?

No

Programs

CS528 is a completion requirement for:
  • (from the following course set: )
  • (from the following course set: )