This message, related to the development of the theme, only displays on the localhost homepage to notify you of any important theme changes.

Version 1.1.0 - May 18, 2020

With this version, the theme has fully implemented static search using lunr.js. That being said, a few modifications were necessary to implement this feature.

To utilize this, or future version of Hugo Future Imperfect Slim, please make the following changes:

  1. Add the following to your config.toml before [params]:
disableLanguages = [""]

    home = ["html", "json"]

  1. Remove the underscore from all about and contact page file names: -->

  2. Add layout = "about" or layout = "contact" to all of the files you just just adjusted the file names for.

While I realize this is inconvenient, I hope that it is worth it to you in the long run. Thanks for using the theme, and feel free to submit issues as needed.

David Neuzerling

David Neuzerling

Data, Maths, R

I have a machine learning model that takes some time to train. Data pre-processing and model fitting can take 15–20 minutes. That’s not so bad, but I also want to tune my model to make sure I’m using the best hyper-parameters. With 16 different combinations of hyperparameters and 5-fold cross-validation, my 20 minutes can become a day or more.

Locking down R package dependencies and versions is a solved problem, thanks to the easy-to-use renv package. System dependencies — those Linux packages that need to be installed to make certain R packages work — are a bit harder to manage.

I’ve set myself an ambitious goal of building a Kubernetes cluster out of a couple of Raspberry Pis. This is pretty far out of my sphere of knowledge, so I have a lot to learn. I’ll be writing some posts to publish my notes and journal my experience publicly. In this post I’ll go through the basics of Kubernetes, and how I hosted a Plumber API in a Kubernetes cluster on Google Cloud Platform.

It’s no secret that I love R and begrudgingly use Python. But there’s a another option for data science, and it promises the speed of C with the ease of use of R/Python. That language is Julia, and it’s a delight to use. I took some time to learn the basics, and I’m sharing my impressions here.

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