Name: Edmund Leibert III
Type: User
Bio: .NET, Python, Azure, and AWS enthusiast enamored with building elegant applications and data pipelines π¨π½βπ»π οΈ
Twitter: edmund_leibert
Location: California, United States of America
Blog: https://edmund-leibert.dev
Edmund Leibert III's Projects
Anki's shared backend and web components, and the Qt frontend
AstroNvim is an aesthetic and feature-rich neovim config that is extensible and easy to use with a great set of plugins
A prototype implementation of Bao for PostgreSQL
C++ Documentation
DEGENESIS: Rebirth system for Foundry Virtual Tabletop
Special repository to showcase, via a README, who I am to the wider world! π
π΄ An Anki plugin for Obsidian.md
Talk to others using a language you can speak and scrambles text you can't understand.
The minimal amount of CSS to replicate the GitHub Markdown style
Simple interactive visualizer to understand Kadane's algorithm
A launch point for Edmund Leibertβs personal nvim configuration.
Neovim config for the lazy
Leetcode Custom Themes for Code Editor
Scraper to evolve into mind map
To be used for the assignments in Cogs 108
Blazing fast Neovim framework providing solid defaults and a beautiful UI, enhancing your neovim experience.
An Obsidian plugin that adds banners to your notes
An Obsidian.md plugin that makes creating and configuring callouts easy.
A plugin for Obsidian which enables converting highlights, underlines, bolded texts, or any selected texts into clozes.
Obsidian Plugin : Assign colors to tags. Has integrations with other plugins, like Kanban.
A minimal and aesthetically pleasing font color menu that makes adding color to your fonts much easier π§βπ¨.
A plugin to edit and view Excalidraw drawings in Obsidian
Phonological rule learning using program synthesis
Final Project materials and description.
π± a fast, batteries-included static-site generator that transforms Markdown content into fully functional websites
π Hunt down social media accounts by username across social networks
This repository provides data and scripts to use Sherlock, a DL-based model for semantic data type detection: https://sherlock.media.mit.edu.