This is the landing page for my notes.

This is 100% inspired by Andy Matuschak's famous notes page. I'm not technically skilled enough to replicate the full "Andy Mode", though, so I just did some simple hacks. If you're curious how these notes compiled, check out the summary in How these notes are made into HTML pages.

This is my "notes garden". I tend to it on a daily basis, and it contains some of my less fully-formed thoughts. Nothing here is intended to be cited, as the link structure evolves over time. The notes are best viewed on a desktop/laptop computer, because of the use of hovers for previews.

There's no formal "navigation", or "search" for these pages. To go somewhere, click on any of the "high-level" notes below, and enjoy.

  1. Notes on statistics
  2. Notes on differential computing
  3. The State of Data Science
  4. Network science
  5. Scholarly readings
  6. Software skills for data scientists
  7. The Data Science Programming Newsletter MOC
  8. Life and computer hacks
  9. Reading Bazaar
  10. Blog drafts
  11. Conference Proposals

How these notes are made into HTML pages

Like almost every creative endeavour in life, this website was duct-taped together using a combination of unreleased Python packages living in Git repositories and custom Python scripts. The Markdown files are authored in Obsidian.

Credit has to be given where credit is due, so let's try that:

  • @kmcgillivray who made obsidian-lettersmith
  • @gordonbrander who made [lettersmith], a very lightweight and very well organized collection of tools to transform text. (Right up the alley of Composable program transforms), except now we're talking about "text transformations".
  • Obsidian's devs for making everything so portable and hackable. I ❤️ what they are doing with the development of effectively an IDE for notetaking. Keep up the good work, y'all.

State of Data Science

Network science

A collection of my thoughts on Network science and visualization.

Things I've made:

A thought: Use position, order, and color in graph visualizations.

Data Science Programming Newsletter MOC

With the Data Science Programming newsletter, I'm trying to share ideas on how to make

Key information


  1. On last week of the month, draft newsletter.
  2. On every first Monday of the month, send out the newsletter.
  3. Cross-post to essays collection.