While at NYCDSA, Spencer has strengthened his engineering and data science skills through a variety of projects. He has created a music recommendation application called Muse that utilizes a form of weighted nearest neighbors and leverages both Spotify and Youtube’s API’s to fetch relevant music videos to the attribute variance of a user’s playlist. For his capstone project, Spencer built an application called Enigma where users can upload their own data and easily create an stacked ensemble model through a step by step visual interface. With each step, Enigma filters a 3D three.js network graph of models, refines summary statistics and visuals, and even suggests optimal models. Enigma was built using R, Caret, Python, Flask, React, Three.js, and Webpack.