Thomas Sherk's Projects
Third assignment for CPS 151. We created a calculator that implemented linked lists and designed a GUI that allows the user to perform calculations such as addition, subtraction, multiplication, and boolean operations.
Assignment 2 for CPS 151. We created a converter to convert between Lbs and Kilograms as well as Fahrenheit and Celsius. We also created a calculator that does basic operations.
I will be uploading my code that I used to participate in this year's (2019) NFL big data bowl which is located here: https://www.kaggle.com/c/nfl-big-data-bowl-2020. I published a kernel of features that I created for the competition here: https://www.kaggle.com/sherkt1/final-hole-metric-features-v5-0. I will publish my submission kernel when the submission window has ended.
This repository is for the assignments that I completed for the class Computer Vision. Assignment 2 applies Hough transformation, Cannyedge, Expectation Maximization, and K-Means segmentation to images fed into the script. Assignment 3 applies HaarCascade to detect faces. Final Assignment applies sift to detect facial features. Photobooth applies various kernels such as Gaussian kernels or edge detection kernels to image data fed in through a webcam and returns it to the screen.
Welcome to the GitHub repository for the CPS596 Survey Application, a dynamic web-based tool designed for academic research. The purpose of the survey is to capture user data related to prefrences regarding images generated by AI tools. The website is currently under construction but can be reached here: http://172.233.209.33:8080/
This is the ebook that another student and I created for Professor Mary Fuhs' pilot study. The ebook is a counting game that asks the user to pick which side of a book shows more animals. The game records statistics for each game including things such as response time, answer, and number of animals shown on each side as well as others.
HW1 For CPS561 Fall 2023. Notes can be found in the README
This is a repository for class MEE 537-01 Final Project. My group has decided to create a music visualizer that reacts to a predicted output by a genre classification CNN. The user plays a midi-keyboard and the notes are converted to an input and fed through the CNN - the visualizer receives the output and does "something".
This repository includes everything related to my final year project involving the tv show SharkTank which was eventually published. For the project, I created models to predict whether a startup would 'strike' a deal with the 'sharks'. Paper, presentation, dataset, code, and figures included.
Stock market app for ios. Pulls data from various news outlets and market data from polygon.io and displays it in app built using Flutter.