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Conference: KubeCon + CloudNativeCon Europe 2022
Authors: Stephen Batifol, Ed Shee
2022-05-18
tldr - powered by Generative AI
Creating a machine learning platform that optimizes for both data metrics and business metrics is a challenge. The platform should be easy to launch and iterate, have common tooling and infrastructure, and prioritize automation and monitoring. The goal is to make machine learning a core business component.
- Disconnect between data metrics and business metrics is a challenge for data scientists
- Machine learning platform should optimize for both data metrics and business metrics
- Platform should be easy to launch and iterate
- Common tooling and infrastructure is important
- Automation and monitoring should be prioritized
- Machine learning should be a core business component
Conference: KubeCon + CloudNativeCon North America 2021
Authors: Dylan Wilder Patterson, Haytham Abuelfutuh
2021-10-15
tldr - powered by Generative AI
The presentation discusses the differences between DevOps and ML Ops, and how Flight can help with ML Ops workflows.
- ML Ops has different requirements than DevOps, such as dealing with large amounts of data and longer processing times
- Flight is a platform that can help with ML Ops workflows, providing features such as composition, caching, and validation
- Flight can handle individual containers for task execution environments, but not yet streaming data
- Flight has been well-received by data scientists for its ease of use and out-of-the-box parallelism