Location: Brendan Iribe Center, Room 1116
The Division of Information Technology (DIT) at the University of Maryland is pleased to announce the following workshop for members of the University community. During this hands-on, lunch-and-learn workshop, a MathWorks engineer will introduce fundamental machine learning and deep learning concepts with “low code” MATLAB techniques. Through hands-on practice, you will learn how to import pre-trained deep-learning networks in MATLAB and retrain these networks (transfer learning) on different datasets. This workshop will also review steps to determine whether a machine-learning or deep-learning approach will best suit your data modeling needs as well as compute resources available to you through the university.
There are only a limited number of seats available. Registration will remain open until 18 November 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.
The workshop is open to all members of the UMD community.
Prerequisites
Some basic familiarity with MATLAB is assumed. If you are not familiar with MATLAB or want a refresher, you might wish to take the free self-paced MATLAB Onramp course from MathWorks (about 2 hours).
System Requirements
This is a bring-your-own-laptop style event. It is not required to have MATLAB installed on your laptop since we will use MATLAB Online for this workshop; use your UMD credentials to sign in.
If you want to have MATLAB, including the ML/Statistics and DL Toolboxes, installed on your laptop, you may download it at no charge on Terpware.
Resources
In case Terpware encounters issues, you may download a recent MATLAB version (e.g. R 2022b or R2023b) from the UMD MATLAB portal as hosted by MathWorks.
The difference between Mahine Learning and Deep Learning is briefly explained in this YouTube video.