Hey there :)
I'm Christine
and most days
I'm sporting a
messy bun
AND
getting stuff done.

about CHRISTINE GARVER

Education

I graduated from Northwestern University in 2020. I double majored in Computer Science and Statistics.
I studied abroad in London at King's College in the Fall of 2018!

Relevant Classes: Machine Learning, NLP, Intro. to AI, Data Mining & Analysis, Advanced Algorithms, Internet Systems, Database Systems, Data Visualization, Bayesian Statistics, Regression Analysis, Human-Computer Interaction, Data Structures & Algorithms, Statistical Methods, Computational Photography, and more!

Interests/Hobbies

In my free time, I enjoy running, listening to music, playing lacrosse, and web design.
Alternative and pop music are my favorite music genres. I like to listen to Kacey Musgraves, Dua Lipa, The 1975, and Post Malone.

Where I'm From...Where I Want to Go

I was born and raised near San Francisco... I love California, but I wanted to live in a different city during college and I instantly fell in love with Chicago.
I like using data to help drive decision-making. I'm also interested in learning more about ethics and bias in data science and algorithms.

A Couple of Resources that Have Educated Me on the Biases in AI, Algorithms & Data Science

I recommend checking out Joy Buolamwini and Timnit Gebru's paper, "Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification" (Buolamwini & Gebru, 2018), the Algorithmic Justice League, and watching "Coded Bias" to learn more about the dangers of bias in AI and algorithms. I also found Chelsea Barabas' article about 'studying up' very insightful: "Studying Up: Reorienting the field of algorithmic fairness around issues of power". Let me know if you have any other books, movies, podcasts, etc. that further teach about the bias in technology!

Technical Skills

Python

C++

R

HTML/CSS

GitHub

Microsoft Office

SQL

Adobe Photoshop

Links

GitHub
LinkedIn

PROJECTS

Boston Marathon Analysis

Since I love running, I decided to analyze
running data from the Boston Marathon (2015, 2016, 2017).
I got the data from kaggle.com. I had fun using my EDA skills to find patterns in running data. I also tried predicting finish times and ages of runners
but I didn't have enough features and I mainly wanted to focus on EDA. In the future, I hope to analyze and model training running data!! I also want to learn to create more advanced visuals (animated graphs, heat maps, etc.).
Click the link below to see how I think through exploratory data analysis.

:) Boston Marathon

La Liga & Messi Data Visualization

I used a shiny app to display statistics about La Liga and Messi's shots versus Real Madrid.
Both plots introduced me to a deeper understanding of ggplot, and how to deploy a shiny application.
I learned how to visualize data in a clear manner
If you click the links below, you will be redirected to my projects. Data was taken from Kaggle.

:) La Liga App
:) Messi Goals App

Tweet Sentiment Analysis Platform

During Summer 2019, I used logistic regression to classify tweets as
happy or sad. I'm still working to improve the accuracy of the model.
Click the link below to be directed to the project:

:) Tweet SAP

Query Search Classifier

I experimented with 5 different machine learning algorithms in R
to ultimately choose one classifier to predict relevance of a website.
This project is a very basic 'web query search', but it
introduced me to bootstrapping, random forests, SVM, and
how to use R to perform classification. The link below will download a PDF of my project:

:) Basic Web Query Classifier

Let's keep in touch!
Thanks for visiting!
Please reach out
to me for a resume,
or with any
questions, suggestions, etc.

 SEND EMAIL to
christinegarver19@gmail.com