Data Science in Production: Packaging, Versioning and Continuous Integration
A common pattern in most data science projects I participated in is that it’s all fun and games until someone wants to put it into production. All of a sudden the crucial question is how to deploy your model, which version, how can updates be rolled out, which requirements are needed and …
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