This is the site for Scott Sievert, a graduate student studying large-scale machine learning at UW–Madison. I think Python is pretty sweet 🐍 and love to ski 🎿!
I tend to blog about technical topics, including interesting mathematics and cool applications of Python.
All my posts are listed at Blog and organized with tags at Tags. Links to follow this blog are in the footer. I list some of my favorite posts at Favorite posts, and they're marked with a ☆. Here's a random favorite post:
Here's some of my recent posts:
Visualization of the COVID-19 infection rates
Data on the infection rate is difficult to find. This post will present some data sources and show some visualizations of the infections. It’ll also provide some tips on how to avoid coronavirus.
This post will be updated frequently (hopefully daily).Read on →
Better and faster hyperparameter optimization with Dask
- describe “hyperparameter optimization”, a common problem in machine learning
- describe Hyperband’s benefits and why it works
- show how to use Hyperband via example alongside performance comparisons
In this post, I’ll walk through a practical example and highlight key portions of the paper “Better and faster hyperparameter optimization with Dask”, which is also summarized in a ~25 minute SciPy 2019 talk.Read on →
- Launching tasks from workers with Dask
PyTorch: fast and simple
I recently came across PyTorch, a new technology prime for optimization and machine learning. The docs make it look attractive, so immediately I wondered “how does it compare with NumPy?”
Turns out it’s a pretty nice framework that’s fast and straightforward to use. I’ll detail the speed before talking about ease-of-use.Read on →
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