Deploying end-to-end machine learning workflows​ with HPE Ezmeral ML Ops.mp4

FESCH.TV INFORMIERT:

Explore the fundamentals of HPE Ezmeral ML Ops, a container-based software platform that helps operationalize ML workflow processes to deliver ML models to production with ease. By building an ML pipeline that implements a basic end-to-end data science workflow to predict travel times for a NYC taxi ride using given data points, you’ll learn how it can be used to enable data science teams, reduce times to deliver models, and enhance collaboration between data science and operations teams.