Azure Machine Learning Designer

What is Azure Machine Learning Designer?

Azure Machine Learning Designer (formerly known as Azure ML Studio (classic)) provides a visual drag‑and‑drop interface to build, train, and deploy machine‑learning models without writing code. It integrates seamlessly with Azure resources, enabling scalable, reproducible pipelines.

Key Features

• Visual pipeline authoring with over 250 built‑in modules.
• Seamless data import from Azure Blob Storage, Azure Data Lake, and on‑premises sources.
• Automated ML integration for hyperparameter tuning.
• One‑click deployment to Azure Container Instances, AKS, or as a Web Service.
• Versioning, experiment tracking, and model management via Azure ML workspace.

Quick Start

1. Sign in to the Azure Portal and create an Azure Machine Learning workspace.
2. Navigate to Designer from the workspace overview.
3. Drag a Data Input module onto the canvas and connect to a dataset.
4. Add a Train Model module, select an algorithm, and connect the data.
5. Add a Score Model and Evaluate Model to test accuracy.
6. Click Submit to run the experiment.
7. Once satisfied, click Deploy to publish as a web service.

Sample Pipeline

# No code required – this is a visual pipeline description
[Dataset] → [Clean Missing Data] → [Normalize Data] → 
[Split Data] → [Train Model (Logistic Regression)] → 
[Score Model] → [Evaluate Model] → [Deploy Web Service]