Computer Science 692S - S-Systems for Machine Learning

Machine learning is employed in an increasingly wide range of applications. Using ML entails developing end-to-end pipelines to collect data, clean it, and run learning and inference algorithms in a scalable manner. This results in computationally intense workloads and complex software pipelines. Systems for ML help users organize their data and scale these computationally intense problems to larger and larger datasets. At the same time, ML is having an increasing impact on systems design. Fine-tuned heuristics and cost models are being replaced by learned models, following trends observed in other fields. This seminar will review cutting-edge research on these topics and allow students to work on a hands-on project. This course will primarily involve reading, presenting, and discussing papers (for 1 credit), and a final project building a machine learning pipeline (for 3 credits).

Open to Graduate Computer Science students only. SECT 01=3 CR; SECT 02=1 CR. SEATS HELD FOR INCOMING GRAD STUDENT REGISTRATION. STUDENTS NEEDING SPECIAL PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.