I gave a talk at Pydata DC 2018 where I tried to articulate some reasons why companies building machine learning products under-invest in engineering and architecture. I’m very interested in feedback, pointers to other resources on this topic, and a general discussion about how to make more effective ML products.

Open in Google Docs

And the video: