Here are my portfolio projects.
Predicting Adult Income: An End-to-End Machine Learning Pipeline Project
This project uses the Adult Income dataset to explore how demographic and work-related factors influence earnings. Through feature engineering, a custom transformer creates a new “workload level” variable that captures the relationship between education and weekly work hours. Using a scikit-learn pipeline, multiple models are tested, with Logistic Regression emerging as the most efficient and…
Predicting Presence of Liver Cancer Using Logistic Regression
This project details the process of creating a logistic regression model on a set of synthetic clinical data for the purpose of predicting if a patient has or will have liver cancer. This project includes a detailed EDA section and many visualizations and detailed process explanations and result interpretations.
Transforming Organizational Training: A Mixed Methods Change Initiative in the U.S. Defense Sector
This project details the design and execution of an organizational training needs assessment study. Using a custom mixed methods model, quantitative and qualitative data were collected and analyzed, giving leaders a full picture of what changes were needed.
Forecasting Stock Market Index Prices Using Linear Regression
This is a practical example of implementing linear regression in python: forecasting stock index prices. This project includes data sourcing, wrangling, exploration, feature engineering, visualization, ML model training and testing, prediction, and brief mathematical explanations.
Advanced Analysis of Categorical Data in Python
This project demonstrates the process of re-engineering categorical data to work for a particular business case. Then, advanced analysis and visualization were used to reveal the stories these data wanted to tell. Tools used: Python, Jupyter Notebook, pandas, glob, numpy, matplotlib, seaborn
Michael G. Sullivan 