Bio: By day I work at RC, by night I mind my quartet of cats.

Addis Augmented

made by Tamrat, submitted by rachel
Addis Augmented explores and documents historical, architectural and urban artifacts in the city of Addis Ababa through augmented reality.

An introduction to functional programming

made by maryrosecook, submitted by rachel
This is a clear explanation of functional programming concepts using Python and practical examples.

Webring 2020: Webrings for the 21st century

made by amy_cheng, submitted by rachel
This is a fun example of productive nostalgia: a way to create webrings in JavaScript!

Recreating Retro Plotter Art

made by piratefsh, submitted by rachel
In this talk at Plotter People, Sher Minn explores computer history, the first plotters and the graphics folks make with them, and some neat examples of fractals and emergent patterns.

Repominder

made by simon-weber, submitted by rachel
Repominder is a Django project that reminds OSS maintainers when they've forgotten to cut a release.

Dynamicland Experiments

made by cwervo, submitted by rachel
This is a great collection of projects and experiments created at Dynamicland, a great place.

Restoring RC's Color Classic

made by davidbalbert, nicholasbs, submitted by rachel
RC has a small collection of vintage computers. Occasionally folks restore them, and do fun stuff like this!

FOIA The Dead

made by parker, submitted by rachel
When someone's obituary appears in the New York Times, FOIA The Dead sends automated requests to the FBI for their records on the recently departed, and publishes the results. So far it has almost 4,000 pages of (sometimes-mundane, sometimes-fascinating) records on 55 people which probably wouldn't have been released otherwise.

My First Emacs Commit

made by nickdrozd, submitted by rachel
Nick describes his first commit to "real-deal core GNU Emacs," with some interesting commentary and historical context.

Using deep learning and Google Street View to estimate the demographic makeup of neighborhoods across the United States

made by tgebru, submitted by rachel
This paper details how Timnit and her team used Google Street View images of cars, deep learning, and neural networks to (accurately!) predict the demographics and political leanings of a neighborhood based on the types of vehicles detected there.