The following are projects completed as graduation requirements for General Assembly's Data Science Immersive Course.
(September 25 - December 22)
I apply Bayesian networks in order to model, predict, and make complex and non-linear inferences on the incidence of shark-human interaction and attacks around the globe.
In this group project, we use Natural Language Processing, unsupervised Latent Dirichlet Analysis for topic modeling, and AWS Rekognition for image recognition in order to analyze the drivers of Twitter engagement.
In response to the Chicago WNV Kaggle Competition, we aim to provide insights on how to better prevent the spread of West Nile Virus in the Chicagoland area.
Using webscraper and a tree-based model, I identify key drivers behind when Reddit posts go viral and make recommendations for how to achieve viral success.
Using Iowa Liquor sales data, I investigate the impact of county-level liquor sales in a controlled beverage state.
This project examines geographic differences in participation in the SAT and ACT and identifies the areas with the greatest opportunities for SAT participation growth.
Current online course: Probabilistic Graphical Models Specialization by Stanford's Daphne Koller, Professor of Computer Science and Co-Founder of Coursera.
Next Hackathon: #ExpeditionHacks Human Trafficking Hackathon: Arlington, VA 2018.
