Industrial-grade ML requires transformation in almost every part of an organization, and as a result, production ML hurdles are often organization-wide hurdles. Teams face challenges ranging from political issues and data product/market fit to limitations with software tools and technology platforms. This talk proposes solutions aimed at tackling these challenges including approaches to project and organizational strategy, in addition to technology platform design.
