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All The Models: An Intro To Solving Sticky Data Science Problems Quickly with CivisML

All The Models: An Intro To Solving Sticky Data Science Problems Quickly with CivisML

by Peter Skipper

We recently released CivisML, our machine learning service in Civis Platform. With it, I can run all the models I’m accustomed to working with, and scale them — off my machine. To get you started, we created the below notebook using publicly available data at the UCI Machine Learning Repository. Feel free to clone the repo on GitHub and check...

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CivisML: Scikit-Learn at Scale

CivisML: Scikit-Learn at Scale

by Stephen Hoover

Late last year, my colleagues on the Social Science team were working on a new survey weighting scheme that would greatly improve the precision of our public opinion data. To make it work, they needed to fit dozens of models for each completed survey. Each survey asks multiple questions, each of which would need to be modeled individually, using an...

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Leading with Data: Civis and the National Technical Information Service

Leading with Data: Civis and the National Technical Information Service

by Mary Lazzeri

For the past two years and up until a few months ago I was part of a unique White House initiative that paired the country’s top technologists with its brightest civil servants, on a joint effort to improve the usability and reliability of Federal government’s critical public services. This illuminating experience gave me visibility across multiple Federal agencies into the...

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Tips and Lessons Learned from Upgrading Ruby on Rails

Tips and Lessons Learned from Upgrading Ruby on Rails

by Jonathan Cobian

In a recent post, I shared a how-to guide on upgrading Ruby on Rails based on my team’s experience in doing so for the Civis Platform. In this post, I’ll share some of the tips and lessons learned around code implementation, third-party libraries, and testing. Hopefully, they’ll help you make your next upgrade easier than your last. Code Implementation Private...

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