Predictive Maintenance

David Smith shows off a predictive maintenance gallery for dealing with aircraft engines:

In each case, a number of different models are trained in R (decision forests, boosted decision trees, multinomial models, neural networks and poisson regression) and compared for performance; the best model is automatically selected for predictions.

On a related note, Microsoft recently teamed up with aircraft engine manufacturer Rolls-Royceto help airlines get the most out of their engines. Rolls-Royce is turning to Microsoft’s Azure cloud-based services — Stream Analytics, Machine Learning and Power BI — to make recommendations to airline executives on the most efficient way to use their engines in flight and on the ground. This short video gives an overview.

Check out the data set and play around a bit.

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Defining Tidy Data

John Mount shares thoughts about the concept of tidy data: A question is: is such a data set “tidy”? The paper itself claims the above definitions are “Codd’s 3rd normal form.” So, no the above table is not “tidy” under that paper’s definition. The the winner’s date of birth is a fact about the winner […]

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Visualizing Earthquake Data

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