Tutorial: Create Training and Inferencing Pipelines with Azure ML Designer

In the first part of this series, I introduced the concept of Azure ML Pipelines. In the current tutorial, we will explore Azure ML’s interactive designer to build training and inference pipelines for a simple machine learning model.

By the end of this tutorial, we will build a binary classification/logistic regression model to predict whether or not a patient has diabetes based on certain diagnostic measurements included in the dataset.

For background on Azure ML, refer to this article and tutorial.

Create an Azure Resource Group and ML Workspace

Start by creating a new ML workspace in one of the supporting Azure regions. Make sure you choose the enterprise edition of the workspace as the designer is not available in the basic edition.

Read the entire article at The New Stack

Janakiram MSV is an analyst, advisor, and architect. Follow him on Twitter,  Facebook and LinkedIn.