Advanced Statistical Machine Learning (Online)

REGISTER HERE Registration will close at 12:01am 4/22/24. No late registrations will be accepted.

This one-day course will be offered via Zoom only. Attendance is required as it will not be recorded.

Description:

Statistical machine learning is an interdisciplinary research area which is closely related to statistics, computer sciences, engineering, and bioinformatics. Many statistical machine learning techniques and algorithms have proven to be very useful for various scientific areas. This course will cover a number of unsupervised learning techniques for finding patterns and associations in Big Data. These include dimension reduction techniques such as principal components analysis and non-negative matrix factorization, clustering analysis and significance analysis, and network analysis with graphical models. The main emphasis will be on the analysis of real data sets from various scientific fields. The techniques discussed will be demonstrated in R.

Intended audience:

This course is intended for researchers who have some knowledge of statistics and machine learning, and want to be introduced to relatively more advanced statistical machine learning topics.

Prerequisite:

Participants should be familiar with matrix linear algebra, linear regression and basic statistical and probability concepts, as well as some familiarity with R programming.

Instructor: Yufeng Liu

Yufeng Liu is currently professor in Department of Statistics and Operations Research, Department of Biostatistics, and Department of Genetics at UNC-Chapel Hill. His current research interests include statistical machine learning, high dimensional data analysis, personalized medicine, and bioinformatics. He has taught statistical machine learning courses multiple times at UNC, as well as short courses on this subject at Joint Statistical Meetings, ENAR, FDA, and Biostatistics Summer Institutes at University of Washington. Dr. Liu serves on the editorial boards for several statistics journals, including as Area Editor for Annals of Applied Statistics, and Associate Editor for Journal of American Statistical Association. He received the CAREER Award from National Science Foundation in 2008, and Ruth and Phillip Hettleman Prize for Artistic and Scholarly Achievement in 2010, and the inaugural Leo Breiman Junior Award in 2017. Dr. Liu is currently an elected fellow at American Statistical Association, Institute of Mathematical Statistics (IMS), and an elected member of International Statistical Institute.

Registration fees:

• UNC Chapel Hill Students: $0, with a $35 deposit to hold your spot (deposit is refundable upon your attendance for at least 66% of the course)
• UNC Chapel Hill Faculty/Staff/Postdoc/Resident/Visiting Scholars: $80
• University (Non UNC Chapel Hill) Student/Employee (must have active university email): $105
• Government/Non-Profit/Corporate: $130

Additional course information:

• Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
• Zoom link for those attending online will be sent prior to the course. Registration must be made at least 3 days prior to the course date to receive the Zoom link.

 

For questions regarding this class, please contact Jill Stevens at jill_stevens@unc.edu