Projects
This page has a sample of projects I’ve worked on. More projects can be found on my GitHub page as well as the code for the projects listed here.
Tackling Churn with ML - Before Modelling
I co-wrote a blog post about how to address customer churn using machine learning and DataRobot and avoid common pitfalls.
Using Supervised Machine Learning to Classify Politicians’ Speech about COVID-19 Restrictions
This was my dissertation for my Master’s Degree in Applied Social Data Science from LSE. The final paper is linked above and you can find more information about the background work on my GitHub.
PySpark Topic Modelling
This project was my final assignment for Distributed Computing for Big Data, a postgraduate course in the LSE statistics department.
South America Tweets Visualization
An Exploration of the Role of Likert Items in School-Based Survey Analysis.
Presented at the annual conference of the American Educational Research Association (AERA), 2019
This paper explores Likert item treatment in school-based surveys. It is common to treat Likert items on education surveys as interval data and perform arithmetic analyses reserved for interval data on this ordinal data. To explore the treatment of Likert items in school-based surveys the items are analyzed as interval and ordinal in two different use cases, 1) survey design and 2) analysis of results. Scale creation is analyzed using principle component analysis (PCA) and categorical principle component analysis (CATPCA). Both CATPCA and PCA yielded comparable results. Survey results are analyzed using a stratified sample t-test and ordinal regression. The t-test approach examines the difference in means. Conversely, the ordinal regression approach treats the data as ordinal. The ordinal regression approach yielded results that are largely consistent with the results from the stratified sample approach.