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Machine Learning
Dive into the world of machine learning on the Databricks platform. Explore discussions on algorithms, model training, deployment, and more. Connect with ML enthusiasts and experts.
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Deployment as code pattern with double training effort?

datastones
Contributor

Hi everybody, I have a question re: the deployment as code pattern on databricks. I found and watched a great demo here: https://www.youtube.com/watch?v=JApPzAnbfPI

My question is, in the case where I can get read access to prod data in dev env, the deployment as code pattern would basically require us to re-do the training all over again on the same prod data that we used for training in dev. This double training effort seems quite redundant to me. Let's assume that the model is relatively time consuming to train, how exactly can we address this with the deployment as code pattern?

Could anyone educate me what I am missing here? Thank you very much!

As companies roll out ML pervasively, operational concerns become the primary source of complexity. Machine Learning Operations (MLOps) has emerged as a practice to manage this complexity. At Databricks, we see firsthand how customers develop their MLOps approaches across a huge variety of teams ...
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Thank you very much for your help, Fatma! I'll take those considerations into account. Cheers.

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