Effective use of RevoScaleR Transformations

As mentioned previously, several important RevoScaleR functions include provisions for transforming data within the function itself, rather than require separate steps in addition to the function call. This is advantageous, since it means that large datasets can be read once instead of having to be read repeatedly by several functions. rxImport, rxDataStep, and rxSplit support […]
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Making Sense of Microsoft’s RevoScaleR Function Parameters

The RevoscaleR functions provided by Microsoft in Machine Learning Server and MS R Client are many and varied, as are the parameters are passed to control their behavior. But while it might seem a bit overwhelming at first, it is really quite simple. Except for the fact that ETL generally reads and writes to multiple […]
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SQL Server 2016 – Analytic Revolution with R: Part 3

Implementing a Data Science Workstation SQL Server Architecture for R and Data Science We have previously seen how to integrate R with SQL Server. While executing R scripts in stored procedures is tremendously valuable, the methods lacks the interactivity required by most analysts. To appreciate how SQL Server’s R services can provide this interactivity, we […]
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