Build machine learning models in a simplified way with machine learning platforms from Azure. Machine learning as a service increases accessibility and efficiency.
Build machine learning models in a simplified way with machine learning platforms from Azure. Machine learning as a service increases accessibility and efficiency.
先导入所有必要的Python模块,包括标准的Scikit-learn模块和Azure ML模块。 复制 import datetimeimport numpyasnpimport pandasaspdfromsklearn.model_selection import train_test_splitfromsklearn.linear_model import LinearRegressionfromsklearn.externals import joblibimport azureml.corefromazureml.core import Workspa...
Webservice.wait_for_deployment 自動調整規模 適用於:Python SDK azuremlv1 為Azure Machine Learning 模型部署處理自動調整的元件是 azureml-fe,也就是智慧型要求路由器。 因為所有推斷要求都會通過該元件,因此其具有自動調整已部署模型的必要資料。 重要
public AzureMLLinkedService withApiKey(SecretBase apiKey) Establezca la propiedad apiKey: la clave de API para acceder al punto de conexión del modelo de Azure ML. Parameters: apiKey - el valor apiKey que se va a establecer. Returns: el propio objeto AzureMLLinkedService. withAuthe...
AzureMLServiceLinkedService AzureMLUpdateResourceActivity AzureMLWebServiceFile AzureMySqlLinkedService AzureMySqlSink AzureMySqlSource AzureMySqlTableDataset AzurePostgreSqlLinkedService AzurePostgreSqlSink AzurePostgreSqlSource AzurePostgreSqlTableDataset AzureQueueSink AzureSearchIndexDataset AzureSearchIndexSink AzureSea...
AzureMLLinkedService(DataFactoryElement<String>, DataFactorySecret) Initializes a new instance of AzureMLLinkedService. Properties 展开表 AdditionalProperties Additional Properties To assign an object to the value of this property use FromObjectAsJson<T>(T, JsonSerializerOptions). To assign an ...
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To optimize performance, use a storage account in the same region that Azure ML service uses. To upload larger files, up to 10 GB, there are several approaches: Use a zipped file.You can upload datasets to Azure ML Studio (classic) in zipped format, and then use theUnpack Zipped Datasets...
model, you can useTrain Modelto train the model on a dataset, like any other learner in Machine Learning. The trained model can be passed toScore Modelto use the model to make predictions. The trained model can then be saved, and the scoring workflow can be published as a web service....