I coded this demo to showcase my final project for a Deep Machine Learning class. For the project, me and a partner trained a type of generative adversarial network (GAN) called a CycleGAN to convert photos into the style of Monet. We combined this with a progressive growing technique for more stable training.
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This is a game engine designed to play and analyze the board game Pente. This project was inspired by my enjoyment of this game, and the absence of other analysis engines online for this game. The algorithm uses a variant of minimax/alpha-beta pruning called principal variation search, in combination with various heuristics I learned about while researching.
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This is a tool that helps you learn to identify birds based on their song and what they look like. It interfaces with the iNaturalist API to provide endless practice examples for any bird on the planet, and automatically links to resources explaining how to identify them. There is also a cool search feature for finding out which birds are commonly observed in your area, and letting you practice those.

This project helped me learn the basics of Figma, which I used to design the user interface (UI) for this app. It is my first mobile-first UI design, and first time I put significant effort into the UI of a website.
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This is a tool I created to help me learn to identify wildflower families. It repeatedly shows you images of wildflowers in my home area pulled from iNaturalist and you have to guess the wildflower family.
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