Casey Cooper
A showcase of my personal projects as well as various data science techniques. My resume can be found on the About Me page.
Portfolio
Here is a collection of my Data Science projects.
Tweet Sentiment Analysis
This project aims to build a machine learning model that can accurately classify a tweet as Positive, Negative, Neutral, Extremely Positive, or Extremely Negative. This project explores the use of common NLP techniques (text pre-processing, TF-IDF Vectorizer with basic classification models, neural networks with learned embeddings)
Sports Betting
This project aims to create a model to predict whether an NFL game goes over or under the total set by sports books with an accuracy of at least 52.4% (this is the percentage that sports bettors need to win at to be profitable). The model is deployed using a Flask app, through AWS in an EC2 instance: https://dev.sbmodel.com/. The GitHub repo can be found here: https://github.com/KOcasey/Sports-Betting.
NLI for Clinical Trials (Coming Soon to Website)
This project explores the use of LLMs for natural language inference. The goal is to create a model to accurately classify whether a statement about a clinical trial entails or contradicts the information in the eligibility criteria, intervention, results, or adverse events sections