Please Join this latest Data Science Central podcast to learn how you can develop machine learning models from an analytics base table and move that model to the edge for the purposes of scoring – or even training. Doing this will help you address latency reductions, security risks, and the potential for the corruption of your real time data. By improving models on the edge, your work will drive more data-driven business decisions faster.
Speaker:
Lorry Hardt, Principal Solutions Architect – SAS
Hosted by:
Rafael Knuth, Contributing Editor – Data Science Central
