Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
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Updated
Jun 5, 2024 - Shell
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance
Launch an MLFlow server through Docker
Run tidyverse, tidymodels, targets, carrier, and MLFlow within Docker
Hera is a Python framework for constructing and submitting Argo Workflows.
Building ML pipeline with Kubernetes(minikube)
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
Add a description, image, and links to the mlops-workflow topic page so that developers can more easily learn about it.
To associate your repository with the mlops-workflow topic, visit your repo's landing page and select "manage topics."