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[] Primary difficulty
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Classroom Contents
MLOps Build or Buy - Startup vs. Enterprise Perspectives
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- 1 [] Aaron and Katrina's preferred coffee
- 2 [] Recommender and System and Jake
- 3 [] Takeaways
- 4 [] Introduction to Aaron Maurer & Katrina Ni
- 5 [] Aaron Maurer & Katrina Ni's Recommend API blog post
- 6 [] 10-pole machine learning use case and Rex's use case
- 7 [] Genesis of Slack's recommender system framework
- 8 [] The Special Sauce
- 9 [] Speaking the same language
- 10 [] Use case sources
- 11 [] Slack's feature engineering
- 12 [] Main CTR models
- 13 [] Data privacy
- 14 [] Slack's recommendations problem
- 15 [] Fine-tuning the generative models
- 16 [] Cold start problem
- 17 [] Underrated
- 18 [] Baseline
- 19 [] Cold sore space
- 20 [] LLMs in Production Conference Part 2 announcement!
- 21 [] Data scientists transition to ML
- 22 [] Unicorns do exist!
- 23 [] Diversity of skill set
- 24 [] The future of ML
- 25 [] Model Serving
- 26 [] MLOps Maturity level
- 27 [] AWS Analogy
- 28 [] Primary difficulty
- 29 [] Wrap up
