From 69521567666b02c2d17ac23c948456a8ad813cda Mon Sep 17 00:00:00 2001
From: Amrutha
-When deploying ML model in Python there are two core questions. The first is will it be real time and whether the model is a deep learning model. For deploying deep learning model that require real time we recommend Azure Kubernetes Services (AKS) with GPU. For a tutorial on how to do that look at [AKS w/GPU](https://github.com/Microsoft/AKSDeploymentTutorialAML). For deploying deep learning models for batch scoring we recommend using AzureML pipelines with GPUs, for a tutorial on how to do that look [AzureML Pipelines w/GPU](https://github.com/Azure/Batch-Scoring-Deep-Learning-Models-With-AML). For non deep learning model we recommend you use the same services but without GPUs. For a tutorial on deploying classical ML models for real time scoring look [AKS](https://github.com/Microsoft/MLAKSDeployAML) and for batch scoring [AzureML Pipelines](https://github.com/Microsoft/AMLBatchScoringPipeline)
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+When deploying ML model in Python there are two core questions. The first is will it be real time and whether the model is a deep learning model. For deploying deep learning model that require real time we recommend Azure Kubernetes Services (AKS) with GPU. For a tutorial on how to do that look at [AKS w/GPU](https://github.com/Microsoft/AKSDeploymentTutorialAML). For deploying deep learning models for batch scoring we recommend using AzureML pipelines with GPUs, for a tutorial on how to do that look [AzureML Pipelines w/GPU](https://github.com/Azure/Batch-Scoring-Deep-Learning-Models-With-AML). For non deep learning model we recommend you use the same services but without GPUs. For a tutorial on deploying classical ML model for real time scoring look [AKS](https://github.com/Microsoft/MLAKSDeployAML) and for batch scoring [AzureML Pipelines](https://github.com/Microsoft/AMLBatchScoringPipeline)
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From fa9f17c5acd16715b14fdf3444f26c8dc5874ee0 Mon Sep 17 00:00:00 2001
From: Amrutha
-When deploying ML model in Python there are two core questions. The first is will it be real time and whether the model is a deep learning model. For deploying deep learning model that require real time we recommend Azure Kubernetes Services (AKS) with GPU. For a tutorial on how to do that look at [AKS w/GPU](https://github.com/Microsoft/AKSDeploymentTutorialAML). For deploying deep learning models for batch scoring we recommend using AzureML pipelines with GPUs, for a tutorial on how to do that look [AzureML Pipelines w/GPU](https://github.com/Azure/Batch-Scoring-Deep-Learning-Models-With-AML). For non deep learning model we recommend you use the same services but without GPUs. For a tutorial on deploying classical ML model for real time scoring look [AKS](https://github.com/Microsoft/MLAKSDeployAML) and for batch scoring [AzureML Pipelines](https://github.com/Microsoft/AMLBatchScoringPipeline)
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+When deploying ML model in Python there are two core questions. The first is will it be real time and whether the model is a deep learning model. For deploying deep learning model that require real time we recommend Azure Kubernetes Services (AKS) with GPU. For a tutorial on how to do that look at [AKS w/GPU](https://github.com/Microsoft/AKSDeploymentTutorialAML). For deploying deep learning models for batch scoring we recommend using AzureML pipelines with GPUs, for a tutorial on how to do that look [AzureML Pipeline w/GPU](https://github.com/Azure/Batch-Scoring-Deep-Learning-Model-With-AML). For non deep learning model we recommend you use the same services but without GPUs. For a tutorial on deploying classical ML model
+
+
+ for real time scoring look [AKS](https://github.com/Microsoft/MLAKSDeployAML) and for batch scoring [AzureML Pipelines](https://github.com/Microsoft/AMLBatchScoringPipeline)
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