The short answer is: _you don't_. That's not how machine learning works at scale. To quote from a great recent article: (I can't find the link, sorry) It's on

The short answer is: _you don't_. That's not how machine learning works at scale. To quote from a great recent article: (I can't find the link, sorry) It's one thing to create an excellent fraud detection model in R, and quite another to build: - Fault-tolerant ingest of live data at scale that could represent fraudulent actions - Real-time computation of features based on the data stream - Serialization, versioning and management of a fraud detection model - Real-time prediction of fraud based on computed features at scale - Learning over all historical data - Incremental update of the production model in near-real-time - Monitoring, testing, productionization of all of the above You don't build a data team out of a single person and tack on an easy model to build a company - it takes a team to build a real data project, and those teams are hard to find, hard to recruit, and hard to make successful.