Ml-Monitoring on Ethan Rosenthal

ML Monitoring with Materialize

Tue, 19 Jul 2022 00:00:00 +0000

In my last post, I strongly encouraged monitoring Machine Learning (ML) models with streaming databases. In this post, I will demonstrate an example of how to do this with Materialize. If you would like to skip to the code, I have put everything in this post into AIspy, a repo on GitHub.

DTCase Study

Let’s assume that we are a machine learning practitioner who works for Down To Clown, a Direct To Consumer (DTC) company that sells clown supplies. A new user who lands on our website is called a lead. When that user purchases their first product, we say that they converted.

Let's Continue Bundling into the Database

Tue, 10 May 2022 00:00:00 +0000

A very silly blog post came out a couple months ago about The Unbundling of Airflow. I didn’t fully read the article, but I saw its title and skimmed it enough to think that it might’ve been too thin of an argument to hold water but just thick enough to clickbait the VC world with the word “unbundling” while simultaneously Cunningham’s Law-ing the data world. There was certainly a Twitter discourse.

They say imitation is the sincerest form of flattery, but I don’t know if that applies here. Nevertheless, you’re currently reading a blog post about data things that’s probably wrong and has the word “unbundling” in it.

Starting Up and Shutting Down, Quickly

Wed, 22 Jan 2020 00:00:00 +0000

There is no shortage of stories about tech founders achieving face-melting wealth from startup success. Bless their hearts.

On the other side are stories with unhappy endings of founders sacrificing everything for the sake of their startup. I hate those stories.

This story lies smack-dab in the middle. There is zero money made and minimal money lost. This is a story of how I had an idea that I was excited about, pursued it for 6 months, and then decided to pull the plug and get a job.