Creating Models in Azure Machine Learning Studio Designer
Creating Models in Azure Machine Learning Studio Designer looks at how to create model training pipelines using a no/low code graphical designer. This lesson describes the differences between the two designer options, Classic prebuilt and Custom, before showing how to build a simple pipeline that sources data, cleans it, and uses a classification algorithm to train a model.
Once trained, we use scoring and evaluation components to assess the model’s prediction accuracy. The lesson aims to equip students with practical skills in model training within Azure ML Studio, leveraging its graphical interface for a streamlined experience.
Learning Objectives
Learn the difference between Classic prebuilt and custom designers
See how to train a model using prebuilt components
Evaluate a trained model’s accuracy
Intended Audience
Students wanting to know how to train models without writing scripts
Prerequisites
While not a prerequisite, Implementing Pipelines in Azure Machine Learning discusses creating custom components that can be used with the custom designer
Hallam is a software architect with over 20 years experience across a wide range of industries. He began his software career as a Delphi/Interbase disciple but changed his allegiance to Microsoft with its deep and broad ecosystem. While Hallam has designed and crafted custom software utilizing web, mobile and desktop technologies, good quality reliable data is the key to a successful solution. The challenge of quickly turning data into useful information for digestion by humans and machines has led Hallam to specialize in database design and process automation. Showing customers how leverage new technology to change and improve their business processes is one of the key drivers keeping Hallam coming back to the keyboard.