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ML Flow vs Kubeflow 2022 // Byron Allen // Coffee Sessions #108

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CHAPTER

How Do You See Machine Learning Playin Around With Machine Learning?

The sematic layer is a management of what youd normally end up displaying in an indivdualization tool or use an imput to ano model. The advantage that you'd get is that you could consolidate that between your your a pipe lines and your visualization. So if you're trying to predict the number of users, you can use that same number of users defined once in a d b t query,. Use it in your m pipe lines for some time serious predictions, and use that in your visualization tool with something like superset. And as a sort of new data scientist joining a team, and it'll be your one stop shop for any data that you need.

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