We talked about:

Marysia’s background
What data-centric AI is
Data-centric Kaggle competitions
The mindset shift to data-centric AI
Data-centric does not mean you should not iterate on models
How to implement the data-centric approach
Focusing on the data vs focusing on the model
Resources to help implement the data-centric approach
Data-centric AI vs standard data cleaning
Making sure your data is representative
Knowing when your data is good enough
The importance of user feedback
“Shadow Mode” deployment
What to do if you have a lot of bad data or incomplete data
Marysia’s role at PyData
How Marysia joined PyData
The difference between PyData and PyCon
Finding Marysia online


Links:

Embetter & Bulk Demo: https://www.youtube.com/watch?v=L---nvDw9KU


Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp
Join DataTalks.Club: https://datatalks.club/slack.html
Our events: https://datatalks.club/events.html