在以下示例脚本中,我们预配了 Linuxcompute cluster。 可以查看Azure Machine Learning pricing页面,了解 VM 大小和价格的完整列表。 我们需要对此示例使用 GPU 群集,因此让我们选择一个 STANDARD_NC6 模型并创建一个 Azure 机器学习计算。 Python fromazure.ai.ml.entitiesimportAmlCompute gpu_compute_target ="gpu-cl...
在以下示例脚本中,我们预配了 Linuxcompute cluster。 可以查看Azure Machine Learning pricing页面,了解 VM 大小和价格的完整列表。 对于此示例,我们只需要一个基本群集;因此,我们选取一个具有 2 个 vCPU 内核和 7 GB RAM 的 Standard_DS3_v2 模型来创建 Azure 机器学习计算。
.models.get(name=registered_model_name, version=latest_model_version) # define an online deployment # if you run into an out of quota error, change the instance_type to a comparable VM that is available.\ # Learn more on https://azure.microsoft.com/en-us/pricing/details/machine-learning...
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Online endpoint deployment is ideal for applications that require real-time predictions, such as fraud detection, predictive maintenance, personalisation and predictive pricing. Deployments Deployment in Azure Machine Learning involves taking a trained and tested machine learning model and making...
You'll be billed separately as per AACS pricing for such use.Work with models not in the model catalogFor models not available in the model catalog, Azure Machine Learning provides an open and extensible platform for working with models of your choice. You can bring a model with any ...
Visualizing and exploring the results of your Azure Machine Learning Studio (ML Studio) experiments is useful both when developing and evaluating the model but most importantly when deploying your model and presenting the results. With Power BI Desktop this can be done in two ways, ...
Machine Learning Maintenance Managed Applications Managed DevOps Pools Managed Grafana Managed Identity Managed Services Management Groups Maps Maps Creator Maps Management MariaDB Marketplace Catalog Marketplace Ordering Media Services Mixed Reality ML Studio (classic) Mobile Network Monitor MySQL Network Gatew...
Visualizing and exploring the results of your Azure Machine Learning Studio (ML Studio) experiments is useful both when developing and evaluating the model but most importantly when deploying your model and presenting the results. With Power BI Desktop this can be done in two ways, ...