Who Puts Your Machine Learning Models in Production?
When building Machine Learning (ML) products, what is the common output from the following three agile objectives? Build things fast Build things right Build the right things Answer: A useful and reusable model. No MVP without a model in production. And production is not the final easy step after proving model value in a notebook. It’s not merely an […]
Exploring digital art with CSS-only
Let’s start with what CSS-only means. It’s exactly what it sounds like, making things appear in a browser using nothing but HTML divs and CSS. So no code, no libraries, no dependencies, super easy right? Now obviously I’m not talking about fully functioning web applications (though I have seen some mocked out to an incredible degree). […]
Why you need MLOps to build agile ML products
Most Machine Learning (ML) models never reach production. They stay in notebook experimentation heaven where everything is about data science. A proof of concept ML model in a notebook is one thing. Going from a notebook to production is a whole other ball game. It requires the entire end-to-end data and ML pipeline to be […]