The Clemson Deep Learning project was one of three projects for the Fall 2017 senior design/capstone. Each Capstone project
has a team of students that work in an agile environment to produce a deliverable by the end of the semester. Nvidia
gave two Tesla P100 GPU's to the Capstone program to be used for deep learning. The project envoled determining compatible
hardware for the GPUs to make a server, researching and finding useful material to help others get started and to create
two interesting showcases that uses deep learning. While waiting on the parts for the server, our team did installation
of deep learning frameworks and the showcases on Caleb's Nvidia workstation.
If you are interested in the Clemson Capstone program contact:
Dr. Alexander Herzog at
aherzog@clemson.edu
Fall 2017 Clemson Deep Learning Team:
Angelo Carrabba I chose this project because I wanted to learn about deep learning in depth and the math behind it. I finalized the
hardware recommendations for the server and created the Google DeepDream showcase.
Emilie Whitesell I heard about deep learning because I was interested in autonomous driving but I wanted to know what else deep learning
was capable of and how it worked. I set up Jupyter Notebook on the workstation and created the Deep Learning website.
Jake Roose I wanted to understand how this revolutionary technology works so that I can help apply it to different fields. I worked
on creating the interactive aspect of the colorization showcase and implemented an image recognition CNN.
Jacob Kaufmann I believe most of the technological innovation that will occur in my lifetime will be a result of AI. I was the team
representative, installed Caffe, Digits, and Cuda on the workstation, and researched trends in deep learning.
Kylon Tyner I wanted to learn more about deep learning because it is one of the most popular trends in computer science right now.
I created the Colorization project with having a grayscale image input and getting a colored image as output.