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[] Feature Stores' current landscape
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Classroom Contents
Unpacking Three Types of Feature Stores - MLOps Podcast
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- 1 [] Simba's preferred coffee
- 2 [] Takeaways
- 3 [] Coining the term 'Embedding'
- 4 [] Dual Tower Recommender System
- 5 [] Complexity vs Reliability in AI
- 6 [] Vector Stores and Feature Stores
- 7 [] Value of Data Scientists
- 8 [] Scalability vs Quick Solutions
- 9 [] MLOps vs LLMOps Debate
- 10 [] Feature Stores' current landscape
- 11 [] ML lifecycle challenges and tools
- 12 [] Feature Stores bundling impact
- 13 [] Feature Stores and BigQuery
- 14 [] Virtual vs Literal Feature Store
- 15 [] Hadoop Community Challenges
- 16 [] LLM data lifecycle challenges
- 17 [] Personalization in prompting usage
- 18 [] Contextualizing company variables
- 19 [] DSPy framework adoption insights
- 20 [] Wrap up