These meetings are offered every semester, and are tailored for the newcomers to the club. These are what, initially, @jmuchovej, @flxsosa, and @dibaccory, offered at club meetings.
The goal of this course is to compensate for the lack of UCF undergraduate coursework
in intelligence and related fields (e.g. machine learning, computational neuroscience,
etc.). As a semester offering, the overarching idea is that the course material won't
change much, but each semester will entail a slight twist on the presentation, as
expected with rotating instructors.
Within each <sem><year> (e.g. sp19) folder, there's an env.yml file, which can be
used with Anaconda. These have only been tested on Linux systems, so
version numbers may not be up-to-date on platforms which don't use the Linux Kernel.
However, the usage of such env.yml files will be detailed below.
$ conda env create -f <sem><year>/env.yml$ conda activate ucfai-<sem><year>NOTE: We assume the use of GPU versions of Deep Learning libraries (e.g. PyTorch, TensorFlow, etc.). If you do not have a GPU, then you should install the CPU versions of said libraries.