Credentials
Coding Projects
A few of the personal and school projects I've worked on recently. Check back soon for updates!
AI Bartender - A custom drink recommendation engine for use at a cocktail and wine bar. AI portion is functional; interface still in progress. Uses RAG with custom menu data to describe and recommend drinks both on- and off-menu based on user's provided preferences and/or mood.
Skills/tools used - HuggingFace Inference API, RAG, Prompt Engineering, Data wrangling, Structured Data, HTML/CSS/Javascript, Various AWS Services
The "Analyzer" - An "analysis" app that does almost nothing, but does it with style. Written over a weekend to prep for a job interview, its main goal was to get me accustomed to a few new technologies, most notably Java/Maven, GraalVM, and multiple Docker microservices communicating via API.
Skills/tools used - Analyzer: Python, Pandas/Matplotlib, Docker, Backend: Flask, Java, Maven, GraalVM, Docker, Frontend/Hosting: HTML/CSS/JS, Bootstrap, AWS S3 + EC2, NGINX
Portfolio Website - At risk of getting recursive, this is the project you're currently viewing. I built this website from scratch, and it is registered with and hosted on AWS. Candidly, some AI assistance was used for the web design.
Skills/tools used - HTML, CSS, Bootstrap, AWS Route 53 + Cloudfront, AWS S3, Responsive Web Design, AI Assisted Web Development
Streamlit A* Search - To present some of my code for non-technical users, I used Streamlit to make a simple purely-python webapp demonstrating A* search. The real value, though, was practicing a complete deployment pipeline: github -> docker -> nginx -> AWS EC2 -> AWS Route 53 -> you!
Skills/tools used - Python, Streamlit, Git/Github, Docker, Nginx, Ubuntu Server, AWS EC2, Search Algorithms
Davis_ai Github Repository - Most of my coding work has been done in a combination of Python and Jupyter Notebooks. This repository contains some custom ML classifiers for school project use, along with a visual guide for each, and an example of a fully-documented KNN notebook.
Skills/tools used - Python, Jupyter notebooks, Pandas, Numpy, Scikit-learn, Matplotlib, Seaborn, Data exploration and processing, Git/GitHub
Spelling Bee Solver - A simple webapp that solves the New York Times' Spelling Bee puzzle. It may not be the most flashy tool, but my mother plays Spelling Bee every day, so building a way to trounce her every day was fun. I also got some practice with some web tools I don't use often enough.
Skills/tools used - Python, Flask, RESTful API, Gunicorn, Nginx, AWS EC2, HTML/JS/CSS
C++ Address Book - Most of my undergraduate-level CS work was done in C++, and this serves as a pretty good demo of what I learned during that time. It is an OOP-style CLI app that creates and maintains a simple address book. Emphasis is on data structures, search and sorting algorithms, custom serialization, and OOP techniques such as classes and class templates.
Skills/tools used - C++, CLI, Templates, OOP, Data Structures, Serialization