Real-Time Machine Learning: Features and Inference - MLOps Podcast #135

Real-Time Machine Learning: Features and Inference - MLOps Podcast #135

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[] Sasha's and Rupesh's preferred coffee

1 of 17

1 of 17

[] Sasha's and Rupesh's preferred coffee

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Real-Time Machine Learning: Features and Inference - MLOps Podcast #135

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  1. 1 [] Sasha's and Rupesh's preferred coffee
  2. 2 [] Takeaways
  3. 3 [] Changes in LinkedIn
  4. 4 [] "Real-time" Machine Learning in LibnkedIn
  5. 5 [] Value of Feedback
  6. 6 [] Technical details behind getting the most recent information integrated into the models
  7. 7 [] Embedding Vector Search action occurrence
  8. 8 [] Meaning of "Real-time" Features and Inference
  9. 9 [] Are "Real-time" Features always worth that effort and always helpful?
  10. 10 [] Importance of model application
  11. 11 [] Challenges in "Real-time" Features
  12. 12 [] System design review on Pinterest
  13. 13 [] Successes of real-time features
  14. 14 [] Learnings to share
  15. 15 [] Branching for Machine Learning
  16. 16 [] Not so talked about discussion of "Real-time"
  17. 17 [] Wrap up

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