This provides an overview of the Azure Machine Learning Service. A browser based workbench for the data science workflow, which includes authoring, evaluating and publishing predictive models. Visit Azure Machine Learning Documentation to learn more.
This video introduces Azure Machine Learning Studio, a visual tour of the Azure Machine Learning studio workspaces and collaboration features. Visit What is Azure Machine Learning Studio? to learn more.
Azure Machine Learning supports R. You can bring in your existing R codes in to Azure Machine Learning and run it in the same experiment with provided learners and publish this as web service via Azure Machine Learning. This video illustrates how to incorporate your R code in ML studio. Visit…
Data preprocessing is the next step in data science workflow and general data analysis projects. This video illustrates the commonly used modules for cleaning and transforming data in Azure Machine Learning. Visit Machine Learning Documentation to learn more.
This video walkthroughs steps needed to provision an Azure Machine Learning workspace from the Azure Portal. Visit Troubleshooting guide: Create and connect to an Machine Learning workspace to learn more.
Azure Machine Learning API service enables you to deploy predictive models build in Azure Machine Learning studio as scalable, fault tolerant Web services. Azure ML API service leverages Microsoft Azure for deployment, hosting and management of the Azure ML web services. Two types of services can be…
Data Access is the first step of data science workflow. Azure Machine Learning supports numerous ways to connect to your data. This video illustrates several methods of data ingress in Azure Machine Learning. Visit Import training data to learn more.