Multiple Languages, One Team: Bringing R and Python Together

by Michael Heilman

More Data More Problems: Variable Selection with Multiple Response Variables

by Sam Weiss

More data isn’t always better! This post will go over why and how we removed uninformative variables from a modeling dataset using a custom-built neural…

Our Journey to SOC 2 Type II Compliance and How You Can Do It Too

by Rich Lee

From Science to Production: Unleash your Jupyter Notebooks

by Lori Eich

Data scientists are explorers. They use Jupyter Notebooks, one of the most popular environments for data science analysis, to begin work toward creative solutions to big problems…

Civis Data: The powerful dataset built right into Civis Platform

by Wade Johnston

I work alongside data scientists every day, so I know that data science teams can help their businesses thrive if they have the right tools and the best, most…

How the Robin Hood Foundation Uses Data Science to Fight Poverty

by Scarlett Swerdlow

Two of the most effective federal anti-poverty programs in the United States are the Earned Income Tax Credit (EITC) and the Supplemental Nutrition Assistance…

You’ve built it, now automate it with Workflows in Civis Platform

by Lori Eich

How We Fine Tuned Lyric Opera’s Marketing Efforts

by Scarlett Swerdlow

Like many nonprofits in the arts, Lyric Opera of Chicago faces the familiar challenges of aging audiences, technological disruptions, and changes in cultural consumption. In response…

An Open Letter to Young Engineers on Writing Code in the Real World

by Saranga Komanduri

Schools teach you how to write code — how to take an idea and turn it into software that does exactly what you want. This is great. It’s fundamental. What…

Moving from exploration to production with Notebooks and Scripts

by Marshall Miller

When it comes to data science code, there are two sides to the story. There’s the part where you do the exploratory science — and there’s the part where you put…