I18n (Internationalization) has never been simpler to implement using Google Sheets and Python.

With the expansion of SciTeens curriculum program, we decided to set out to create our own Jupyter Notebook autograder for our website.

My contempt for Batch Normalization and love of Dropout layers led me to upgrade pre-trained convolutional neural networks in the simplest fashion possible.

An in-apartment aquaponics system for growing herbs.

A Transformer-based model that paints using emojis. You can provide images or emojis to paint with, and it will attempt to recreate images using emojis.

This package provides a command-line tool for interracting with Leetcode to create flashcards for study, which can then be imported into Anki.

A Fake Wordle clone that lets you input your stats.

A class-based library for generating 3D rendered synthetic data. This library allows for a myriad of control over the specifics of the rendering engine, including but not limited to lens field of view, rendering angle, and mode by which to load a background and/or 3D model to be rendered. This library is also fully extensible, and can be installed from PyPi.

A simple-to-use command-line tool for quickly working with synthetic data. With a directory of background images and another with object files and accompanying textures, you can quickly generate thousands of synthetic images to supplement any dataset. This library interfaces with the Blender bpy library.

The website for SciTeens Inc. Built using NextJS with Server Side Rendering, with a Firebase backend, Google Kubernetes hosting, Google Functions, and OAuth 2.0 for backend operations, and search powered by Algolia. Website is actively maintained.