ML 工作室 (傳統) 文件即將淘汰,未來將不再更新。 在本教學課程中,您會深入瞭解開發預測性分析解決方案的程式。 您在 機器學習 Studio 中開發簡單的模型(傳統版)。 接著,您會將模型部署為 機器學習 Web 服務。 此已部署的模型可以使用新的數據進行預測。 本教學課程是 三部分教學課程系列的第三部分。 假設您...
開啟 機器學習 Studio (傳統) 首頁 (https://studio.azureml.net)。 單擊視窗左上角的功能表,單擊 [Azure 機器學習],選取 [Studio],然後登入。 按兩下 視窗底部的 [+新增 ]。 選取[ 數據集]。 選擇從本機檔案。 在[ 上傳新的數據集] 對話框中,按兩下 [瀏覽],然後尋找 您所建立german.csv 檔案。
Confira informações sobre como mover projetos de machine learning do ML Studio (clássico) para o Azure Machine Learning. Saiba mais sobre o Azure Machine Learning A documentação do ML Studio (clássico) está sendo desativada e pode não ser atualizada no futuro. Neste artigo, você...
Beginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources. Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) resources. See information on moving machine learning projects from ML Studio (classic) to ...
This tutorial walks you through the process of getting data, configuring an algorithm, training and then using a model: Create your first machine learning experiment How to use Train Model In Machine Learning Studio (classic), configure a classification model or regression model models. You can ...
ML Studio (classic) documentation is being retired and may not be updated in the future. Trains a classification or regression model in a supervised manner Category: Machine Learning / Train Note Applies to: Machine Learning Studio (classic) only Similar drag-and-drop modules are available in A...
微软的目标是简化使用机器学习的过程,以便于开发人员、业务分析师和数据科学家进行广泛、便捷地应用。这款服务的目的在于“将机器学习动力与云计算的简单性相结合”。AML目前在微软的Global Azure云服务平台提供服务,用户可以通过站点:https://studio.azureml.net/ 申请免费试用。
Sign into Microsoft Azure, open Azure Machine learning service, select the workspace (that was created as part of the prerequisites) and launch the studio. In the left pane, select Automated ML under the Author section. Select +New automated ML job ...
We also announced that managed MLflow is generally available on Azure Databricks and will use Azure Machine Learning to track the full ML lifecycle. The combination of Azure Databricks and Azure Machine Learning makes Azure the best cloud for machine learning. Databricks open sourced Databricks Delta...
The sample ML model and even its related trainer console app were created with the ML.NET CLI. In fact, you could create the same ML Model and trainer console app by following this ML.NET CLI tutorial. This is basically the code generated by the CLI in that tutorial and what we’re ...