Some Pitters and Patters with R | Simon P. Couch

Analyzing my own music listening data with R and the tidyverse (2023)

All of my friends are posting their Spotify Wrapped, and I’m jealous.

Predicting flight delays with tidymodels🛩

Trying out a variety of machine learning models to predict flight delays out of Madison, WI.

Quarto!

I recently rebuilt this site with Quarto.

Down the submodels rabbit hole with tidymodels

Debugging something that turned out not to be a bug at all.

Hiking the 2023 John Muir Trail / Nüümü Poyo

A group of buddies and I walked 242 miles from Mt. Whitney to Yosemite Valley.

Optimizing model parameters faster with tidymodels

A couple small changes can greatly speed up the hyperparameter tuning process with tidymodels.

Moving On From Baltimore

After 2 years in Baltimore, I recently made the move to Chicago, IL.

The tidymodels is getting a whole lot faster

Recent optimizations have made fits on small datasets much, much snappier.

Analyzing my own music listening data with R and the tidyverse

All of my friends are posting their Spotify Wrapped, and I’m jealous.

Redirecting from sub-domains with Netlify

After merging two websites that deployed from different branches, I had to figure out how to redirect my old blog posts to their new home.

{infer} v1.0.0 is on CRAN

Some short reflections on working on the {infer} R package.

Applying to the NSF Graduate Research Fellowship (GRFP)

A compilation of the advice that made me feel most informed and confident while applying for the NSF Graduate Research Fellowship.

Pipe-esque Programming with {ggplot2}’s Plus Operator

Writing iterative code with ‘+’ rather than ‘%>%’ was a tough transition my first time around.

Big Things (Developer Documentation pt. 4)

On the tension between documenting R packages exhaustively and maintainably.

Naming the Things (Developer Documentation pt. 3)

Weighing the pros and cons of several possible schemas for naming the core functions in {stacks}.

Splitting Things Up (Developer Documentation pt. 2)

Why {stacks} requires (at least) four separate functions to build an ensemble model rather than wrapping them all up into one.

How {stacks} Came To Be (Developer Documentation pt. 1)

Introducing a set of blog posts reflecting on the development process of the {stacks} package.

What’s Next For Me

Applying to Graduate School in Statistics and Biostatistics

There were all sorts of tips and tricks about applying to grad school that I was only able to learn about via office hours, personal meetings, and Twitter DMs, and I thought it would be worth publicly compiling some lessons learned.

Running R Scripts on a Schedule with GitHub Actions

Some pointers on running R scripts and committing their results to a GitHub repository on a regular interval using Actions.

{stacks} v0.1.0 is on CRAN!

Introducing ensemble learning to the tidymodels.

Programatically Generating PDF Reports with the Tidyverse

In a few different roles over the past few years, I’ve come across the problem of programatically generating some kind of PDF reports from data. Here are some tips/tricks I’ve come across while making that happen.

A Gentle Introduction to Tidy Model Stacking

Model stacking is an ensembling technique that involves training a model to combine the outputs of many diverse statistical models. The stacks package implements a grammar for tidymodels-aligned model stacking.

The Blog Thing! We’re Doing It!

For a while now, I’ve wished I had a place to share some short posts on what I’m up to related to R, data science, and statistics. I decided I’d take a Sunday to get this subdomain up and running!

Reuse

https://creativecommons.org/licenses/by-sa/4.0/