Azure Machine Learning Workspace Creation

This repository demonstrates four different methods to create an Azure Machine Learning workspace:

1. Azure Portal: This method involves using the Azure Portal web interface to create a new Azure Machine Learning workspace. Detailed step-by-step instructions are provided in the Azure Portal Method guide.

2. Azure CLI: The Azure Command-Line Interface (CLI) allows you to create an Azure Machine Learning workspace using command-line commands. Refer to the Azure CLI Method guide for detailed instructions.

3. Azure Python SDK: The Azure Python SDK provides a powerful way to programmatically create an Azure Machine Learning workspace using Python code. Check out the Azure Python SDK Method guide for code examples and instructions.

4. ARM Templates: Azure Resource Manager (ARM) templates enable you to define and deploy Azure resources, including an Azure Machine Learning workspace, using declarative JSON templates. The ARM template is shown only as an example but it is possible to create a workspace from it. Here is how you could do it.

Choose the method that suits your needs and follow the respective guide to create your Azure Machine Learning workspace.

Prerequisites

Before you begin, make sure you have the following prerequisites:

• An Azure subscription
• Access to the Azure Portal, Azure CLI, or Azure Python SDK, depending on the method you choose

Contributing

If you would like to contribute to this repository, please make a Pull Request.