I used the Python Reddit api wrapper (PRAW) to create a script that collects post titles from a given subreddit and subsequently uses machine learning via Pythons natural language processing toolkit to determine the overall mood of the subreddit. The final product is two wordclouds repersenting the most common positive and negative words from the sample.
For this study on professional League of Legends I gathered and analyzed information the League of Legends pro scene to determine the most prevalent trends in this multi-million-dollar industry. I also used machine learning to make a model of the most influential variables for predicting who would win a match.
In this project I compare the data on solar flares on an official NASA website with another site to create a more extensive and accurate database.
Using gapminder data on life expectancy across several countries I study trends in life expectancy over time and the interaction between time and country.
This React/Node/MongoDB web app is a class project I created that models the frontend/server/database structure of a website by allowing a user to create edit and delete a genereic ticket object from a database.
A simple Javascript form I made for class. There is server code to go with it but it isn't hosted.
A website I worked on along with peers to create an anonymous messaging board akin to the ubiquitous YikYak/Whisper with the added restriction that it is only available to students at my school. We used a waterfall methodology along with Git to create and add features and fix bugs.
In this project I used both a single Gaussian and Gaussian mixture model to train a classifier to identify an orange ball in a series of images where the ball is placed at different distances and subsequently estimate those differences. This project was developed for use by the school robotics team.
This Matlab script uses the Harris corner detection to find corners in images.