Getting Started with Azure Machine Learning

This guide offers a straightforward pathway to getting started with Azure Machine Learning, making it accessible for beginners.

Hafeez Baig
8 steps
29 seconds

Azure

Type **Azure Machine Learning** in the search bar and click on the **Azure Machine Learning**

**What is Azure Machine Learning?** **Azure Machine Learning** is a cloud-based platform by Microsoft for building, training, deploying, and managing machine learning models at scale. It supports both code-first (using Python, Jupyter, etc.) and low-code (drag-and-drop) approaches. The platform provides tools for automated ML, MLOps, model versioning, and integration with popular frameworks like PyTorch and TensorFlow.

**Azure Machine Learning** page will open, click on the **Create** dropdown from the top left side and click on the **New workspace** option

Scroll to the **Resource group** section and click on the **Create new** link

**What is a Resource group in Azure?** A **Resource Group** in Azure is a logical container that holds related resources for an Azure solution, such as virtual machines, databases, and networks. It helps organize resources based on lifecycle, permissions, and cost management, allowing you to deploy, manage, and monitor them as a unit.

Type "**machine-learning-rg**" and click on the **OK** button

Type "**machine-learning-1-in28minutes**" in the Name placeholder

Scroll the page and click on the **Review + create** button

After the **Validation** is succeed, scroll the page and click on the **Create** button **Note:** It will take some time to create the Azure ML Workspace

**Note:** If the deployment fails, try selecting a different region. Azure sometimes restricts free tier deployments or instances in specific regions due to capacity limitations.

Congratulations on successfully creating Azure Machine Learning Workspace!

Refer to this lab to continue learning - <https://scribehow.com/viewer/Automated_Machine_Learning__Dataset_and_Compute__7i9CwjoOTAeJLe4DjsbWAA>