MLOps is a set of processes that can help today’s organizations get value from data science by reducing friction throughout pipelines and workflows. However, implementing MLOps is easier said than done because it touches so many teams, people, and processes across the organization — it’s larger than just model monitoring in production. Through his experience working with global organizations on governance and MLOps topics, Mark will outline the key components of a robust (and successful) MLOps strategy.
Please note that the original session happened in April 2021 and was accessible to subscribers of O'Reilly's learning platform. This is a recording, so the polls and other interactive elements will not be available.