DataTalks.Club

Data-Centric AI - Marysia Winkels

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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

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