Analytics at Scale: h2o, Apache Spark and R on AWS EMR
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...
Red Oak Strategic - Time Series Forecasting with Machine Learning
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.
Red Oak Strategic - Exploratory Data Analysis: CDC's 500 Cities Project
Introduction
In Part 1, we built an application to geographically explore the 500 Cities Project dataset from the CDC. In this post, we will demonstrate other exploratory data...
Red Oak Strategic - How To: Add & Execute Python Excel Macro
Frequently, we encounter projects that require the combined use of Python, Microsoft Excel and some external databases that can only be accessed via Excel, or use cases that...
Could Google and Xbox solve all of polling’s problems?
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...
Uber & Lyft: Using campaign data science to succeed
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...
The Analytical Nomination Pathway: Proportionality and a Draft Kings Approach
After last night’s Republican debate in Wisconsin, we thought it would be useful to begin analyzing how the GOP campaigns are thinking analytically about their pathways to the...
Why Polling, Data & Analytics Will Finally Converge in 2016
Lots of discussion and criticism came out of this past Tuesday’s election results, much of it focusing on the Kentucky Governor’s race and the lack of reliable polling...