In mid-February, I made a really big life decision, which was to officially leave academia and, really, everything I’d ever known professionally, and accept a position in industry as a data scientist. It’s now been a bit over six weeks since I officially started, and I felt like it was time for some reflections tl;dr Academia often gets a bad wrap, and I understand that completely. For me personally, it was actually pretty great and I’m very grateful to so many people at the University of Oregon, where I worked.

Hello! It’s been… a while, to say the least. But I wanted to share a new thing I’ve been working on. Specifically, I’ve finally started to move more toward the “R in production” model, and I wanted to share how freaking fantastically awesome the combination of parameterized reports in R Markdown with plumber can be. TL;DR I created the report below using pagedown with some (rather a lot of) custom CSS.

The murders of George Floyd, Ahmaud Arbery, Breonna Taylor, and so, so, so many before them have brought into stark relief that if you have black or brown skin in this country, and particularly the former, you are at far greater risk for losing your life for… existing… than if your skin is white. It’s unacceptable. Infuriating. Enraging. Depressing. As a country, we are mourning these deaths (while, as of the time of this writing, Breonna Taylor’s murderers have still not been arrested).

tl;dr I’ve recently learned a lot about gradient descent, and wanted to share here. I used gradient descent to estimate linear regression models and, by the end, produce gifs like this, showing how the algorithm learns! Intro This term I’m co-teaching an applied machine learning course in R using the {tidymodels} suite of packages. It’s been a great experience because it’s allowed me to dig into topics more deeply than I have previously, and it’s definitely helped me learn and understand the tidymodels infrastructure better.

I’m taking some time off work this week to be with my two girls in their final week of summer. But in that time I started playing around with colors in R a bit and wanted to share some of what I’ve learned, specifically in relation to bivariate color palettes. There is an existing R package, {biscale}, which is probably the simplest way to approach this, but I wanted to dig in a bit more and explore on my own.