This post was originally published on Medium
There’s recently been some interesting opinionated writing in the R statistical programming community about how and when to teach the abstracted, easy-to-use approaches to solving problems, versus the underlying nitty-gritty. David Robinson, Data Scientist at Stack Overflow, …
Read MoreInsights from a Predictive Model Pipeline Abstraction
Nov 7, 2016 · 5 min read · data science machine learning software engineering software architecture programming ·This post was originally published on Medium
When building a complex system, it’s often helpful to think about the design of that system using patterns and abstractions. Architects and software engineers do so frequently, and the experience of implementing predictive modeling pipelines has recently led to a variety of …
Read MoreThe below is a public version of a post originally posted on an internal blog at the Education Advisory Board (EAB), my current employer. We don’t yet have a public tech blog, but I got permission to edit and post it here, along with the referenced code.
Data Science teams get asked to do a lot of different sorts of …
Read MoreI just returned from the useR! 2012 conference for developers and users of R. One of the common themes to many of the presentations was integration of R-based statistical systems with other systems, be they other programming languages, web systems, or enterprise data systems. Some highlights for me were an update to …
Read MoreIn my previous post, I motivated a web application that would allow small-scale sustainable meat producers to sell directly to consumers using a meat share approach, using constrained optimization techniques to maximize utility for everyone involved. In this post, I’ll walk through some R code that I wrote to …
Read MoreA few months back I gave a presentation to the NYC R Meetup. (R is a statistical programming language. If this means nothing to you, feel free to stop reading now.) The presentation was on ggplot2, a popular package for generating graphs of data and statistics. In the talk (which you can see here, including both my …
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