Jackson Passey's Projects
gitbook example portfolio
The data, R programming, and outputs for the research paper testing glucose consumption and cognitive factors. I used R to clean, process, model, and visualize the data. The outputs folder contains the finished products. Link to paper pending.
Config files for my GitHub profile.
My blog page about showcasing projects and how-to posts on GitHub.
Random forest and Bayesian Additive Regression Trees (BART) are algorithms considered as optimal supervised learning, non-parametric modeling techniques, each offering powerful tools for predictive analytics. We explore each algorithm process and methodology for handling prediction and classification.
The final project to the STAT 486 Machine Learning Class
The coding and analyses performed from partnered work with Instagram's @UtahStats. You can find the report on Instagram, or find a brief version on my blog.