Airflow's Limitations for MLOps - Challenges and Alternatives

Airflow's Limitations for MLOps - Challenges and Alternatives

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[] Stephen's preferred coffee

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1 of 26

[] Stephen's preferred coffee

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Airflow's Limitations for MLOps - Challenges and Alternatives

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  1. 1 [] Stephen's preferred coffee
  2. 2 [] Introduction to co-host Joe Reis
  3. 3 [] Takeaways
  4. 4 [] Subscribe to our newsletters!
  5. 5 [] Shout out to our sponsor, Wallaroo!
  6. 6 [] Whatnot
  7. 7 [] Stephen's side hustle
  8. 8 [] Stephen's work breakdown at Whatnot
  9. 9 [] Fundamental tensions in the data world
  10. 10 [] Initial questions to answer that you were on the right path
  11. 11 [] Recommender systems
  12. 12 [] Coordinating with ML teams
  13. 13 [] Daxter
  14. 14 [] Too advanced, more challenging
  15. 15 [] Orchestration layer
  16. 16 [] Decision criteria
  17. 17 [] Human design aspect of Daxter
  18. 18 [] Orchestration layer centralization and sharing knowledge with stakeholders
  19. 19 [] Airflow's Problem and the reception it got on Hacker News
  20. 20 [] Java of the Data World
  21. 21 [] Absence of DAGS
  22. 22 [] Interaction with the software engineering team
  23. 23 [] Different services
  24. 24 [] Modernization
  25. 25 [] Stephen's Philosophies
  26. 26 [] Wrap up

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