As Machine Learning becomes more mainstream, how to handle ML algorithms in production is generating a lot of discussion. How do we move algorithms into the real world from the lab? How often do we re-train models? How do we control versioning of the algorithms?
Listen to Nathan Anneken of 84.51 discuss lessons learned in his talk on Scaling ML Models.