Summary
In this chapter, we discussed the fundamentals of data-centric ML and its origins. We also learned how data centricity differs from model centricity, including the roles and responsibilities of key stakeholders in a typical organization using ML. At this point, you should have a solid understanding of data-centric ML and its additional potential compared to a more traditional model-centric approach. Hopefully, this will encourage you to use data-centric ML for your next project.
In the next chapter, we will discover why ML development has been mostly model-centric until now and explore further why data centricity is the key to the next phase of the evolution of AI.
