Skip to content

Data-centric AI

Leveraging data-centric views to architect a continual system that delivers trust and enables iteration.
Goku Mohandas
· ·

📬  Receive new lessons straight to your inbox (once a month) and join 30K+ developers in learning how to responsibly deliver value with ML.


This lesson is a work-in-progress, so please revisit this page later for a first draft release.

Data-centric AI

Key data-centric views that will enable us to make decisions along the way. We've covered most of these views extensively in previous lectures but now we'll see them in relation to the rest of the workflows for on continual learning system.

data-centric views

These data-centric views all involve data as the first-class citizen, where developers and subject matter experts alike can interact at the data level to make decisions. And with them, we can develop a continual learning system that will guide us on when to update and what exactly to update.

TODO: Lot's more details to add on each of the data-centric views.

To cite this lesson, please use:

    author       = {Goku Mohandas},
    title        = { Data-centric AI - Made With ML },
    howpublished = {\url{}},
    year         = {2021}