This week we dive into the abstractions that we're all trying to layer on top of the core ML processes and workflows. I spoke with Phil Howes, co-founder and chief scientist at BaseTen. BaseTen is a platform that allows data scientists to go from an initial model to an MVP web app quickly.
We got into some of the big challenges he had working to build out the platform, as well as the core issue of iteration speed that motivates why they're building BaseTen.
Phil has experienced quite a few of the industry's end-to-end patterns in the years that he's been working on machine learning and it was great to have that context inform the conversation, too.