cmd-023. projecting voter turnout in midterm elections using machine learning.
PROJECT COMPLETED: June 2022
Tools Used:
Python: NumPy, pandas, seaborn, scikit-learn
Google Big Query - used to extract and aggregate census data
Jupyter Notebooks - used to publish the project’s technical documentation
Adobe InDesign - used to create the project’s slide presentation
THE STORY OF THIS PROJECT
I used data from the US Census Bureau and the Georgia Secretary of State’s office to build a machine learning model that predicts voter turnout in midterm elections. My goal was to develop a method of projecting turnout that is more predictive than simply averaging the turnout totals of the last three similar elections.
Final Results:
Stakeholder (non-technical) Slide Presentation: