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Published on Jun 30, 2016
There are a number of ways to get started with machine learning. One of the easiest has been created in the cloud with Azure Machine Learning. Azure ML provides the best of both worlds, an environment to easily apply a variety of different standard machine algorithms while providing the ability to extend the environment to include custom libraries created in R or Python. In this session we will look at what Azure ML can be used for by discussing good cases for the use of this technology. We walk through a model to determine the importance of different criteria, incorporate some SQL code to help model the data and review production deployment options.
Ginger Grant: Having worked with the Microsoft BI stack for many years, Ginger Grant is exploring new challenges by applying her data expertise to the expanding field of data science and data visualization. Using R and Machine Learning she has been able to use data and algorithms to answer many different business questions for users. When not working, Ginger is studying for the pilot degree program Microsoft created for Data Science, blogging at DesertIsleSQL.com and speaking at numerous technical events, including SQL Saturdays, GDI and Women Who Code. An active member of the Microsoft data community, she was recently awarded a Microsoft MVP in Data Platform.