Michelle Tong

Logo

Personal Website

View My GitHub Profile

About

Hi I’m Michelle Tong! I’m currently a fourth-year student at UCSD, diving into the exciting worlds of Data Science and Management Science.

When I’m not buried in academics, you’ll find me grooving to dance beats, solving puzzles, belting out tunes, whipping up some delicious baked goods, immersing myself in games, and getting lost in the world of art. My interests are as varied as they come, reflecting my insatiable curiosity that keeps me on my toes.

I possess a natural intellectual curiosity and a deep desire to continuously expand my knowledge. I am happy to learn about anything you have to share. I am happy to talk about my expertise if you want help. Feel free to connect with me and chat.

An Advocate (INFJ-A) by nature, my personality underscores my empathetic and insightful disposition, allowing me to approach every interaction with a genuine understanding of the human experience. Let’s connect and embark on a journey of shared insights and discoveries.

Contact

Education

Technical Skills

Programming

Java, Python3, SQL, Git, R, Stata, MATLAB, JavaScript, HTML/CSS

Tech Skills

Machine Learning, Data Cleaning & Manipulation, Statistical Modeling & Inference, Supervised and unsupervised learning, Decision Tree

Analytic Tools & Software

Git, Jupyter Notebook, AWS, Microsoft Office

Data Visualization

Excel, Google Sheet, Tableau, Matplotlib, Seaborn, Canva

Languages

Mandarin, Cantonese, English

Work Experience

Data Assistant

University of California, San Diego March 2023 - Present

Data Science Tutor

University of California, San Diego June 2023 - August 2023

Dining Hall Worker

University of California, San Diego October 2021 - June 2022

Barista

T & 5 Bakery June 2019 - September 2021

Chinese School Teacher

Golden Key Chinese School September 2018 - January 2021

Projects

Movie Industry in Pandemic

Undertook an extensive analysis of the movie industry during the pandemic, utilizing data from Kaggle. Employed Excel and Python to preprocess and refine the dataset. Executed exploratory data analysis to uncover correlations between movie revenue and Covid-19 cases as well as vaccination rates.

Developed and optimized multiple machine learning models, including decision trees and random forests, for the purpose of revenue prediction. Rigorously assessed model performance using key metrics like accuracy, precision, recall, and F1-score. Selected the most effective model based on these evaluations, positioning it for potential deployment.

This project underscores my adeptness in data preprocessing, exploratory analysis, and machine learning, all applied to provide valuable insights into the movie industry’s response to the pandemic.

What Happens to Our Electricity?

Website Here

Conducted an in-depth investigation into electricity patterns with a focus on power outages in the United States. Sourced data from Kaggle and orchestrated a comprehensive analysis to discern outage patterns and underlying trends.

Leveraged advanced data visualization techniques including histograms and scatter plots to unveil correlations between power outages and their underlying reasons.

Employed regression analysis and machine learning algorithms to construct a predictive model. Employed optimization strategies like GridSearchCV to fine-tune model hyperparameters. Achieved a remarkable training accuracy of 98% utilizing a random forest model.

This project showcases my proficiency in data exploration, predictive modeling, and machine learning. The ability to uncover insights from vast datasets and predict power outage causes highlights my analytical skills and their practical application in real-world scenarios.

Survival on the Titanic: Predicting Passenger Survival

This odyssey of exploration illuminated profound revelations. Through immersive exploratory data analysis, I unraveled the tapestry of patterns and connections hidden within the data. This revealed a profound nexus between passenger class, age, fare prices, and survival prospects. Building upon this foundation, I engineered a robust classification model, harnessing the potency of random forest trees to predict survival outcomes founded on individual attributes. As the data metamorphosed into visual narratives—encompassing histograms, scatter plots, and decision tree diagrams—the veil was lifted not only on the findings but also on the art of translating complex results into accessible insights for stakeholders. This project stands as a testament to my data-driven prowess and ability to distill intricate findings into comprehensible narratives.