Portfolio
Welcome to my Portfolio! This is where I highlight some of the projects I've worked on.
- Only using
NumPy, I developed a Quadratic Discriminant Analysis (QDA) classifier which identified handwritten digits with 82% accuracy
- Only using
NumPy and SciPy, I built a Random Forest classifier using the Titanic dataset to predict passenger survival with 80% accuracy, based on features such as their position on the ship
- Utilizied
Python, Pandas, and Sklearn to build a classifier which identifies spam emails with 90% accuracy
- Only using
NumPy, I developed a k-Nearest Neighbors classifier to identify movies as Thriller / Comedy with 80% accuracy
- Developed a linear regression model to predict housing prices in Cook County, Illinois
- During the Fall 2024 semester, I taught DATA 198: Introduction to Real World Data Science and utilized Jekyll, Github Pages,
HTML, CSS, Javascript, and Ruby to develop the course website
- Utilized Object Oriented Programming to implement a Plants vs. Zombies inspired tower-defense game called Ants vs. Some Bees
