This portfolio contains a variety of data science projects I have completed. Some of the projects constitute work from the University of Wisconsin Master's in Data Science program. Additional projects were completed as part of my employment at the University of Wisconsin-Madison Division of Extension.
This project was completed to give a high-level understanding of the textual responses in a SWOT survey. This work preceeded in-depth qualitative analysis, and was designed to surface potential avenues of further inquiry.
This project was completed as the final requirement of DS700 - Foundations of Data Science. It presents a time series modeling approach to predictive analytics.
This project was completed as the final requirement for DS705 - Statistical Methods. It uses a classification model to predict loan default.
This project was completed as the final requirement for DS710 - Programming for Data Science. It includes using the Twitter API and statistical analysis of tweets.
This project was completed as part of the final requirement for DS730 - Big Data: High-Performance Computing. It uses Spark in Scala and can be run either in a local Hortonworks environment or on Amazon Web Services.
This project was completed as the final requirement for DS740 - Data Mining and Machine Learning. It uses R to build and assess a machine learning model for predicting opioid use.
This project was completed as part of the course DS745 - Visualization and Unstructured Data Analysis. It uses R to analyze the communication and collaboration network of 80 UW-Madison Division of Extension Employees.
This project was completed as part of the course DS745 - Data Mining and Machine Learning. It uses R to analyze situation statements that were submitted by Extension colleagues as part of their 2019 plans of work. It uses R and various text mining approaches to explore and visualize topics.
This project was completed for the UW-Madison, Division of Extension educators of Bayfield and Ashland counties, and was the capstone project from my degree program. Utilizing two surveys to collect data, exploratory social network analysis, and exponential random graph modeling, I explored the relationships among members of the regional food system. View the Project