CS + Data Science @ NYU • Python / ML • Building data-driven projects
- 🧠 Interested in Machine Learning, applied data science, and scalable pipelines
- 🛠️ I like building end-to-end systems: data → features → machine learning models → evaluation → simple UI
- A project to analyze user chess behavior (style, accuracy, trends) using structured features and ML/LLM tooling.
Current focus: feature engineering, database design, and evaluation pipeline
Tech: Python, SQL, LangChain, Docker, Scikit-Learn
- Scraping + preprocessing + feature engineering + model training + inference pipeline
- Interactive UI for match outcome prediction
Tech: Flask, Python, JS/HTML/CSS, scikit-learn/XGBoost, BeautifulSoup/Selenium
Repo: https://github.com/Youngsang-Cho1/Premier-League-Prediction
- Auth + CRUD + AJAX-driven UI projects
Tech: Node.js, Express, Handle Bars, Bcrypt, MongoDB, REST APIs
Repo: https://github.com/Youngsang-Cho1/Authentication-Based-Academic-Planner
ML / Data
- Supervised learning, model evaluation, feature engineering, embeddings, retrieval
- Pandas, NumPy, scikit-learn, PyTorch (comfortable), Statistics, Calculus, Linear Algebra
Engineering
- Python, JavaScript, SQL, Git
- Flask / Express, MongoDB
- Reproducible workflows, clean codebases, readable docs
- 🎓 NYU • CS + Data Science
- 🌱 Learning more about: LLMs, scalable ML pipelines, and applied research
- 🤝 Open to: research collaboration, internship projects, and building useful tools
Thanks for visiting!