Azure Machine Learning [ML] is a great tool for gathering more insight with your data, but how do you know if the models you are using are providing the best results? How do you apply modules customized to analyze your data? After this session you will have the answers to these questions, as well as the knowledge necessary to implement machine learning data analysis into your data environment.
Using Azure based SQL Server, attendees will learn rules which can be used to classify the data and the type of analysis desired by Azure ML. Building upon this information, the best methods for determining which ML models to use will be shown.
This presentation will demo how to extend the flexibility of Azure ML by implementing custom analysis from other sources. Incorporating items created in R and SQL will show the expanded capabilities available outside of the existing ML components. Lastly we will deploy the Azure ML solution and incorporate the results into our SQL Server Database.
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