Tag Archives: ML Studio

Introducing Microsoft Azure Machine Learning

Microsoft Azure Machine Learning (MAML) is a service on Windows Azure which a developer can use to build a predictive analytics model using machine learning over data and then deploy that model as a cloud service. ML Studio provides functionality to support the end-to-end workflow for constructing a predictive model, from ready access to common data sources, data exploration, feature selection and creation, building training and testing sets, machine learning over data, and final model evaluation and experimentation. In this presentation, we present an overview of the basic data science workflow, with details on select machine learning algorithms, then take you on a guided tour of ML Studio. During the presentation we will build a predictive analytics model using real-world data, evaluate several different machine learning algorithms and modeling strategies, then deploy the finished model as a machine learning web service on Azure within minutes. This end-to-end description and demonstration is intended to provide sufficient information for you to begin exploring ML Studio on your own after the session.

Azure Machine Learning with Parmita Mehta

Azure Machine Learning with Parmita Mehta

In this episode Chris Risner and Haishi Bai are joined by Parmita Mehta, Program Manger on the Azure Machine Learning team.  Parmita gives an overview of the new Azure Cloud Machine Learning Service.  Using the Cloud ML service, Parmita demonstrates how you can create experiments to detect patterns in data.  In the example shown, Parmita uses Cloud ML to predict family income level based off of census data.  This is tested using modules pre-built by MS Research, Xbox, and Bing!  After building and testing out an experiment, Parmita shows how easy it is to push the experiment to production as a web service which can be used to run individual tests or batches.

Links from the show: