Recent Work

NBANeural.net

NBANeural.net is a web interface built in React to view final score projections and "Against the Spread" predictions for NBA games from my machine learning model.

The model itself is a deep learning neural network built in Python using the PyTorch framework. It draws from advanced data metrics that are calculated manually from every play in every single NBA game.

Over several seasons of backtesting, it has consistently reached or surpassed the coveted 55% winning percentage against the spread.

Spotify Playlist Generator

As a personal project to develop my first full-stack application, I decided to work with the Spotify API. I noticed that it had functionality for generating playlists based on multiple songs, artists, or genres, yet there was no way to do this within the Spotify app.

I designed an interface to select up to five songs to base a playlist on, tweak custom "audio features" that Spotify supports, and then generate a playlist that can be automatically added to your Spotify library.

Currently I am not hosting it on a domain, but the code is available on my GitHub page.