Unfortunately, I cannot publish the source code for academic projects on the Internet (with some exceptions). If interested in learning more, please contact me.
Abbreviations:
ML (Machine Learning) - EDA (Exploratory Data Analysis) - SWE (Software Engineering and Optimization) - DB (Database)
ECON 148: Data Science for Economists (Spring 2024)
DATA 102: Data, Inference, and Decisions (Spring 2024)
[ML] [EDA] An Investigation into the Causality of Arkansas Speed Limit Increase on Traffic Accidents and the Effect of Road Conditions on Traffic Accident Duration
Explored various query optimization techniques and learned how to further tune query performance on Lahman’s Baseball Database
[DB] Data Transformation (PostgreSQL)
Utilized multiple data transformation techniques to clean and impute missing data on one month of sensor data from buildings at UC Berkeley Dataset
[DB] MongoDB
Compared different database systems on their handling of semi-structured JSON data using Yelp Academic Dataset
DATA 100: Principles and Techniques of Data Science (Spring 2023)
[ML] Housing Sales Price Predictor
Built a linear regression model that predicts the housing prices in Cook County using feature engineering and cross-validation (500000+ entry housing database)
[ML] Spam Classifier
Built a logistic regression model to predict whether an email was spam or ham. Received a 94% accuracy on the testing set.
Yelp Recommender. Recommends highly rated restaurants to users by categorizing restaurants by their rating. Combines basic supervised and unsupervised learning and object-oriented programming paradigms.
Built a simple 2D game that involves random world generation with seeds, interactions between the user and the game world, a complete user interface, and other basic game features such as progress saving and visual effects.