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Code to take an ML model into production using Feast and Kubeflow

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Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
export		export
feast		feast
fetch		fetch
kubernetes		kubernetes
serve		serve
train		train
README.md		README.md
pipeline.py		pipeline.py

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production_ml

Code to deploy an ML model in production using Feast feature store and Kubeflow Pipelines.

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Code to take an ML model into production using Feast and Kubeflow

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Jupyter Notebook 62.1%
Python 32.0%
Dockerfile 5.9%