Six Stages of Data-Centric MLOps

Servicing an AI system in production requires an engineering approach. What that means is that the operations need to be systematic and repeatable with the necessary tools and processes. You will see that concerns for data need to be at every stage. After these initial questions are answered, we are ready to move to the most important phase of AI development: namely, collecting and labeling data. During the Collecting phase, the goal is to collect data that are privacy-protected, trustworthy, balanced, and diverse.