KaggleX Final Project Presentation with Jessica Pool | Kaggle
About this project: This project focuses on the availability of affordable housing in the United States; in particular, the affordability of already-available housing stock. My research question was: What factors affect the percentage of available homes households making median income can afford? I created a measure of listed home affordability from Zillow home sales and rental data along with median household income and other related information. From there, I tested several regression, classification and machine learning models, while including several economic-related predictor variables in these models, to determine which model best predicts home affordability.
About Jessica Pool: I am Jessica Pool, and I live in Cincinnati, Ohio USA. I earned a PhD in political science from the University of Cincinnati, with a concentration in public opinion and survey research. After earning my degree, I transitioned from academia to industry, currently working at a construction software company in finance and accounting, where I bring analytics into my current role. My goal is to shift into data science as a career, which would allow me to combine my existing statistical research skill set I built in academia with modern data science and machine learning knowledge and tools. I see challenges as opportunities, I really enjoy exploring ideas and problem-solving, and I am passionate about learning new skills, which is why I am drawn to data science. Industry areas of interest include finance, technology, government, and market research.
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About KaggleX: KaggleX BIPOC mentorship program is designed to help increase representation, create career opportunities, and develop individual growth for BIPOC (Black, Indigenous, People of Color) people in the data science industry.
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