Project-Portfolio

Jordan Neumann Project Porfolio

Classification

Rush - Progressive Rock Music

• Rush is a classic rock band that has recorded 165 original songs on 19 studio albums
• Utilized Spotify’s API to extract data about all of the band’s music
• Developed a variety of random forest models to classify whether individual tracks were recorded during the band’s progressive rock era (1974 - 1981)
• View the Github repository here
• View the Kaggle notebook here

Regression

Kaggle Competition - Tabular Playground Series - January

• The task is to predict a bimodal continuous target variable with 14 bimodal or multimodal continuous independent variables
• Submissions are evaluated on the Root-Mean-Squared-Error (RMSE)
• Developed a voting regressor that is comprised of XGBoost and Light XGBoost regressors to minimize the RMSE
• View the Kaggle notebook here

Time Series

Pharmaceutical Sales Forecasting

• The goal of this project is to forecast Colorado’s medical marijuana sales through November 2021
• Adjusted sales for inflation using Consumer Price Index for all urban consumers
• Visualized the data by creating time, seasonal, and autocorrelation plots
• Forecasted data using average, naive, drift, seasonal naive, ETS, and Seasonal ARIMA models
• View the Github repository here
• View the Kaggle notebook here

Visualization

Police Encounters

• The phenomenon of police violence has been at or near the forefront of our public conversation for several years
• Built an interactive dashboard in Tableau to explore data on fatal police shootings in the United States from 2015 through 2020
• View the visualization here
• View the data here

Baby Name Popularity

• Built an interactive application with RShiny to explore the popularity of baby names in New Zealand from 1954 through 2018
• View the live application here
• View the Github repository here

Miscellaneous

PDF-Splitter-GUI

• Created a PDF splitter with a GUI that allows the user to create a new PDF based on a specified page range
• View a demonstration of the splitter here
• View the Github repository here