The Division of Information Technology (DIT) at the University of Maryland is pleased to announce the following workshop for members of the University community.
There are only a limited number of seats available. Registration will remain open until 23 July 2023 or until all seats are filled. Although there is no charge associated with the workshop, we do require registration and we ask that you do not register unless you really intend to attend. Also, if you register and later discover you will not be able to attend, please contact us to cancel your registration as soon as possible so that we can invite someone from the wait list.
NOTE: DIT reserves the right to cancel the workshop for any reason with little notice.
| MATLAB ML/Stat and DL Workshop | |
|---|---|
| Location | Brendan Iribe Center, Room 1116 |
| Date | 25 July 2023 |
| 9:00 AM - 12:00 PM | MATLAB Machine-Learning/Statistics Toolbox |
| 1:30 PM - 5:00 PM | MATLAB Deep-Learning Toolbox |
| Instructor | Evan Cosgrove Education Application Engineer, The MathWorks Inc. |
| Cost | free, registration required |
| Registration Form | link to registration form |
| Application Deadline |
23 July 2023 or when registration is full |
During this hands-on, self-paced workshop, a MathWorks engineer will introduce the Machine-Learning/Statistics and Deep-Learning Toolboxes in MATLAB. By working through common scenarios and workflows using hands-on demos, you will gain a detailed understanding of capabilities of these MATLAB Toolboxes.
The workshop is open to all members of the UMD community interested in developing and performing ML and/or DL tasks using powerful tools.
This is a bring-your-own-laptop style event. Before attending You will want to have a recent version of MATLAB, including the ML/Statistics and DL Toolboxes, installed on your laptop. This is available at no charge to members of the University of Maryland community on Terpware via the campus Total Academic Headcount license.
In case Terpware encounters issues, you may download a recent MATLAB version (ideally R 2022b) from the UMD MATLAB portal as hosted by MathWorks.
The difference between Mahine Learning and Deep Learning is briefly explained in this YouTube video.