Tools for Azure Machine Learning – Machine Learning Fundamental Concepts
Tools for Azure Machine Learning
Azure Machine Learning offers various tools to build your ML solutions. Anyone on an ML team can use their preferred tools to get the job done.
Azure Machine Learning Studio
The Microsoft Azure Machine Learning Studio is the main place where machine learning services in the Microsoft Azure Cloud are run. The original Microsoft Machine Learning Studio Classic will be discontinued in 2024. Microsoft’s Azure ML Studio has steadily gained more features and options over time.
The Azure ML Studio menu can be broken down into its three primary components: author, assets, and manage.
The Author tab is all about writing the code and organizing the infrastructure for your machine learning process.
Assets hold the components, like pipelines, that are developed and saved in the Author tab. It controls the whole process of using the available resources, from the time datasets are put into a pipeline to the time the workflow ends at the endpoints.
The Manage tab is for administering the server infrastructure. It includes data storage, integrations with other systems, and computational clusters and instances.
Azure Machine Learning Designer
Pipelines in Azure Machine Learning are multistep workflows that are used to process data, train models, and manage models. Azure Machine Learning Designer is a visual interface for building ML applications without writing any code. In the Azure Machine Learning Designer, all you have to do to build your ML pipelines is drag and drop.
Azure Machine Learning Designer has more than 60 modules that can be used to change data; input and output data; select features; use statistical functions; do regression, clustering, and classification; train models; and evaluate models. Simply select the modules and connect them, and your pipeline is complete.
