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Analytics at Scale: h2o, Apache Spark and R on AWS EMR

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Mark Stephenson
Thursday, 21 June 2018 / Published in Analytics, Data Science, Machine Learning, Predictive Analytics, R, Tutorials
At Red Oak Strategic, we utilize a number of machine learning, AI and predictive analytics libraries, but one of our favorites is h2o.  Not only is it open-source, powerful and scalable, but there is a great community of fellow h2o users that have helped over the years, not to mention the staff leadership at the
Apache SparkCodeData Scienceh2oPredictive AnalyticsRSparkling WaterTutorials

Time Series Forecasting with Machine Learning: An example from Kaggle

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Matt Brown
Monday, 07 May 2018 / Published in Analytics, Code, Data, Data Science, Forecasting, Machine Learning, Predictive Analytics, R, Tutorials
Introduction This post will demonstrate how to use machine learning to forecast time series data. The data set is from a recent Kaggle competition to predict retail sales.       You will learn how to: Build a machine learning model to forecast time series data (data cleansing, feature engineering and modeling) Perform feature engineering to build
CodeData ScienceForecastingPredictive AnalyticsRTime SeriesTutorials

Could Google and Xbox solve all of polling’s problems?

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Mark Stephenson
Friday, 26 August 2016 / Published in Analytics, Data, Political Analytics, Predictive Analytics
Political polling faces a crisis of confidence. Major news outlets repeatedly ask “What’s the matter with polling?” after major misses like the Bernie Sanders’s primary upset in Michigan, where he beat Hillary Clinton 50–48 despite the fact that she was leading by up to 20 points in reputable polls. There is, however, hope for a
2016 ElectionData SciencePoliticsPolling

Uber & Lyft: Using campaign data science to succeed

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Mark Stephenson
Wednesday, 11 May 2016 / Published in Analytics, Data, Political Analytics, Predictive Analytics
Last Saturday, in what has now been widely publicized and discussed, Uber and Lyft lost an effort, Proposition 1, that would have rolled back a number of regulations on their services. As a result, in one of America’s most forward-thinking tech centers, the services stopped operating almost immediately. Andrew Watts wrote a great analytical piece
Data SciencePoliticsUber

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