Enterprise Workspace Tasks
Question
You are evaluating whether to use a basic workspace or an enterprise workspace in Azure Machine Learning.
What are two tasks that require an enterprise workspace? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.AC
Note: Enterprise workspaces are no longer available as of September 2020. The basic workspace now has all the functionality of the enterprise workspace.
https://www.azure.cn/en-us/pricing/details/machine-learning/ https://docs.microsoft.com/en-us/azure/machine-learning/concept-workspaceAn Azure Machine Learning workspace is a cloud-based environment that serves as a central location for managing machine learning workflows, data, and models. It provides a variety of tools for data scientists, developers, and IT professionals to develop, deploy, and manage machine learning models. Azure Machine Learning offers two types of workspaces: basic and enterprise.
A basic workspace is a lightweight workspace suitable for small teams and projects. It provides essential features such as data preparation, model training, and deployment. An enterprise workspace, on the other hand, is a more comprehensive workspace that offers advanced features such as collaboration, security, governance, and automation.
Regarding the tasks that require an enterprise workspace, the correct answers are C and D.
C. Use a graphical user interface (GUI) to define and run machine learning experiments from Azure Machine Learning designer. Azure Machine Learning designer is a drag-and-drop visual interface that allows users to create machine learning workflows without writing any code. It provides a variety of modules for data preprocessing, feature engineering, model training, and evaluation. An enterprise workspace is required to use Azure Machine Learning designer because it offers collaboration features that allow multiple users to work on the same project, share resources, and track changes.
D. Create a dataset from a comma-separated value (CSV) file. In Azure Machine Learning, a dataset is a collection of data that can be used for training or testing machine learning models. An enterprise workspace is required to create a dataset from a CSV file because it offers advanced data management and governance features. For example, an enterprise workspace allows users to define data schemas, enforce data quality rules, and track data lineage.
In contrast, options A and B do not require an enterprise workspace.
A. Use a graphical user interface (GUI) to run automated machine learning experiments. Azure Machine Learning provides a feature called automated machine learning (AutoML) that allows users to automatically generate and optimize machine learning models. This feature is available in both basic and enterprise workspaces and can be used through a GUI or API.
B. Create a compute instance to use as a workstation. A compute instance is a cloud-based virtual machine that can be used as a workstation for data exploration, model development, and testing. It is available in both basic and enterprise workspaces and can be created using a GUI or API.
