Best Practices for managing Vertex Pipelines code | C2C Community

Best Practices for managing Vertex Pipelines code

  • 11 November 2022
  • 1 reply

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Machine learning pipelines are increasingly being used by organizations to streamline and scale their ML workflows. However, managing these pipelines can be difficult when an organization has multiple ML projects and pipelines in various stages of development. To address this, Google cloud developer advocates suggested that a method be developed to build on DevOps concepts and apply them to this ML-specific problem.

In this post, Google Cloud developer advocates share some best practices for managing the codebase for your ML pipelines based on their work with top Google Cloud customers and partners.

Click on the link below to read it in detail:



1 reply

Userlevel 7
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That's funny!

Yesterday I was at the Cloud Next in Athens, Greece, and one of the speakers, Googler, talked about it.

Thanks for sharing it @malamin 👏