During the second episode of our three-part series, Trevor Royer, Senior Consultant with Red Hat, shares his perspective about model deployment in the context of MLOps, including:

● How to get started with deploying models,

● What options are available for consuming models after they are deployed,

● What considerations to keep in mind with regard to continuous integration and continuous delivery (CI/CD) of deployed models,

● How to determine if a model deployment is successful,

● How development teams and data science teams collaborate effectively, and

● What organizations can do to align development with data science.