• Escrow Smart Contract Deposit ETH into a smart contract, receive an NFT that allows you to withdraw the ETH in after a set duration. No real use case, but wanted to take a stab at learning solidity.

• OHM fork rebase calculator During the height of OHM fork season, I created a tool that could track the rebases on various staked OHM fork tokens. Not as necessary now since most of the forks have collapsed. Coded in python.

• Uber Pickups in NYC WebApp Tested out the Streamlit API to quickly develop and deploy a website that takes Uber data, maps pickups, and allows the user to interact with the graph.

• FastAi Bear Classifier Used machine learning with Bing’s search API to create a webapp that classifies bears as grizzly, black or teddy. Upload a picture of a bear, and it will return the predicted type, and probability that the prediction is correct.

• Rougelike RPG Built a simple rougelike RPG using the libtcod library in Python. Learned about type checking, classes, arrays, and math.

• 2D shooter Used Pygame and built a 2D shooter and levele editor with character animations, looping images, parralax background images, collision detection, very basic enemy AI, and save/load files through pickle.

• DC Zoning Exceptions + Affordable Housing visualization Built a Jupyter notebook that uses geopandas dataframes to plot zoning exemptions + the zoning exceptions that allowed for affordable housing development. Learned about Geospatial Data Structures (essentially a regular pandas dataframe but with a geometry column) and how plotting over maps work.

• Django ecommerce app Built an ecommerce website with Stripe integration using the Django framework. Vendors can sign up and start selling various items. Hosted on replit.com using the “always on” feature.

• Automating alternative data feeds (private repo) Something that we struggled with was centralizing data and bringing in alternative data into our data dashboard platform. Built multiple chron jobs using selenium and beautiful soup to scrape/download data, transform it into a dataframe, and push the dataframe onto our data platform. Here’s an example of water usage data my scripts are pushing into our data platform; since the program runs every hour, it will notify us if there is a surge in usage.