U.S. Election Clustering Analysis
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This project employs unsupervised machine learning techniques to uncover and visualize patterns in county-level voting behavior from the 2016 U.S. presidential election.
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This project employs unsupervised machine learning techniques to uncover and visualize patterns in county-level voting behavior from the 2016 U.S. presidential election.
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A Shiny dashboard simulating the Billboard Hot 100 music chart.
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This project investigates how different demographic and educational factors affect student performance.
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Explored multivariable linear regression modeling using NHANES data to examine the link between alcohol consumption and systolic blood pressure.
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Used Stable Diffusion and CLIP for pediatric chest X-ray classification. Generated synthetic images to address class imbalance and improved model accuracy.
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Analysis of the COVID-19 Case Rate and Excess Mortality Rate by Pandemic Wave
Published in , 1900
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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