Correlating Psychologists Per Capita with Health Data Globally

Goal: Did you know that Argentina has the most therapists per capita, in the world? What makes this the case? The goal of this project was to examine what variables are predictive of the number of mental health workers in a country.

Deliverable: Analysis and visualization of the correlations between health disorders, country GDP and the number of psychologists per capita in the world’s countries. Data collected from the WHO website and the CIA website.

python (pandas, numpy, matplotlib) ~ webscraping

News Corpus Analysis in R

Goal: Compare liberal-leaning and conservative-leaning news media coverage of the weddings of Naomi Biden, and Tiffany Trump.

Deliverable: R program using aggregate sentiment analysis and relative adjective frequency. Findings: conservative-leaning coverage of Tiffany Trump’s wedding was significantly more positively skewed, but there were no significant differences in coverage of Naomi Biden’s wedding between conservative or liberal leaning news outlets.

R ~ Livegap Charts

Training a Model to Predict Loan Defaults

Goal: Using the famous German Credit Data, I trained a boosted decision tree model to classify applicants according to whether they defaulted on their loan. This project demonstrates knowledge of VC theory, a critical topic in data mining.

Deliverable: Python program that implements the Decision Tree Classifier. I fine-tuned the parameters of this model such that it can correctly classify 76% of the applicants.

python (pandas, scikit.learn)