Deploying Predictive Models in Python and R
Nick Elprin, founder of Domino Data Lab, talks about how to deploy predictive models into production, specifically in the context of a corporate enterprise use case. Nick demonstrates an easy way to “operationalize” your predictive models by exposing them as low-latency web services that can be consumed by production applications. In the context of a real-world use case this translates into more subtle requirements for hosting predictive models, including zero-downtime upgrades and retraining/redeploying against new data. Nick also focuses on the best practices for writing code that will make your predictive models easier to deploy.
This video was recorded at the SF Data Mining meetup at Runway.io in SF.