Microsoft Azure Machine Learning (ML) is a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. Azure ML Studio provides rich functionality to support many end-to-end workflow scenarios for constructing predictive models, from easy access to common data sources, rich data exploration and visualization tools, application of popular ML algorithms, and powerful model evaluation, experimentation, and web publication tooling.

This ebook will present an overview of modern data science theory and principles, the associated workflow, and then cover some of the more common machine learning algorithms in use today. We will build a variety of predictive analytics models using real world data, evaluate several different machine learning algorithms and modeling strategies, and then deploy the finished models as machine learning web service on Azure within a matter of minutes. The book will also expand on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services.

The scenarios and end-to-end examples in this book are intended to provide sufficient information for you to quickly begin leveraging the capabilities of Azure ML Studio and then easily extend the sample scenarios to create your own powerful predictive analytic experiments. The book wraps up by providing details on how to apply “continuous learning” techniques to programmatically “retrain” Azure ML predictive models without any human intervention.

Jeff Barnes

Jeff A. Barnes is a Cloud Solution Architect (CSA) on the Microsoft Partner Enterprise Architecture Team, where he engages with leading cloud architects and developers to present Microsoft’s cloud vision. A 17-year Microsoft veteran, Jeff brings over 30 years of deep technical experience to the CSA role. He typically works with key ISVs and global partners to demonstrate how Microsoft Azure technologies can be best leveraged to meet the current and future demands of an organization transitioning to the cloud. Jeff has deep practical experience in the retail, financial, and manufacturing industries and he is a frequent speaker at Microsoft and thirdparty events. Jeff resides with his family in Miami, Florida, where his definition of “offshore development” usually equates to “fishing offshore.”