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Scalable Cross-Platform R-Based Predictive Analytics
In this webinar we will take a quick tour through an end-to-end predictive analytics session. We will start by exploring our data with summaries and histograms. Using the knowledge gleaned from data exploration, we will create transformations to clean our data and prepare it for model building. Next, we will establish a prediction baseline by performing linear regression. Then we will apply a state-of-the-art black box algorithm, Ensembles of Decision Trees, to push prediction to the limit. Finally, we will use this high quality ensemble model to score new data, completing the prediction workflow. We will discover how to perform these steps scalably using an R-based tool across a wide range of platforms: Windows and Linux laptops and workstations, multicore servers, Hadoop and MPI clusters, and massively parallel databases. Presented by Mario Inchiosa, US Chief Scientist for Revolution Analytics.
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