The Center for Statistics and Machine Learning (CSML) is offering a three-hour Wintersession workshop, which aims to increase awareness of how machine learning could aid faculty, postdoc, and student research.
No detailed prior knowledge of machine learning is assumed. The workshop will begin with an overview of crucial machine learning ideas and address three questions: What is machine learning? Where has it been particularly successful? What can it not do well (yet)?
Then faculty, from various parts of the university will give 20-30 minute presentations on how they are incorporating machine learning into their research. The workshop will then move into a question, answer, and discussion session. Several data scientists and a research software engineer will attend this part of the session to answer questions concerning datasets, dataset curation, and software tools for machine learning. The session will target faculty, postdocs, and grad students wondering if machine learning can help their research program. However, space permitting, the session is open to all Wintersession participants.
Boxed lunch provided.
Meet the facilitator:
Peter Ramadge (ECE/CSML): is engaged in research and teaching in signal processing and machine learning with applications in neuroscience. He is the Director of the Center for Statistics and Machine Learning (CSML) at Princeton University.
(Organizer) Brandon Stewart (SOC): develops new quantitative statistical methods for applications across computational social science. Others TBD
What to Expect:
Single workshop (3 hours total)
To request accommodations for this event, please contact the workshop or event facilitator at least 3 working days prior to the event.
- The Center for Statistics and Machine Learning
- Princeton University Wintersession