Some recent projects that I’ve worked on…
*For a more frequently updated list of projects, see my Github repo here.
Project Argo: Built various machine learning models such as spectral clustering, k-means, & gaussian mixture models ran on PySpark’s distributed computing framework to cluster temperature profiles of the fleet of Argo floating buoys around the world. This network of floats monitors temperature, salinity, currents, and bio-optical properties of the world’s oceans, providing sensor measurements for climate and oceanographic research. Data set found here. Our team’s initial project slide-deck found here.
Experimented with different machine learning classifiers for determining iambic pentameter in song lyrics and sonnets. Iambic Pentameter is a type of rhythm or meter in which five small groups of syllables called Iambs or “feet”, which in English are unstressed followed by stressed syllables, are found coupled together. Poem and sonnet data were obtained and cleaned from a variety of sources like Shakespeare, Keats, Frost, Shelley, and Jackson -scraped texts available on the web, while songs from artists such as Taylor Swift and the Backstreet Boys were obtained from Data.World.
Designed a recommendation system in conjunction with PySpark’s Distributed Computing framework that matches classroom charity projects (teachers and their classroom requests) to the most probable donors nationwide. DonorChoose.org in partnership with Google helped provide this data set freely available on Kaggle. Our team’s project slide-deck can be found here.
Dark Market Cocaine Price Prediction: Used various machine learning models to predict the bitcoin price of dark market cocaine. The data set was scraped by a third party and contains approximately 1,400 standardized product listings from Dream Market’s Cocaine category. Our team’s project slide-deck can be found here.