MLOps solution components
01.
Data storage
Azure Blob Storage for data storage.
02.
Model training,
validation, and
registration
Azure Machine Learning workspace.
03.
Model deployment
Azure Machine Learning endpoints and Azure Kubernetes Service.
04.
Model monitor
Azure Monitor for Application Insights.
05.
MLOps pipelines
Azure DevOps and Azure Pipelines.
A standard framework is instrumental in successfully deploying ML models in production.
It plays a pivotal role in managing risks as organizations scale the number of ML applications across various use cases within dynamic environments. Furthermore, it is a steadfast guide to ensure that these applications consistently align with the overarching business objectives, maintaining a harmonious synergy between technology and strategy.
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