Read recent news and blog posts from our team

Aug 5,2016

MVESC: Finding the Missing Students Who Don’t Graduate On Time

August 5th, 2016|

Over 1.2 million or 7.1% high school students drop out every year. Dropping out of high school is costly for both the students and society: 30% of dropouts are unemployed, [...]

Aug 3,2016

CMPD: Behind the Headlines, Beneath the Data

August 3rd, 2016|

It's usual for those of us here at Data Science for Social Good to want to see our projects thrown into the spotlight. More publicity means a wider audience, which [...]

Jul 19,2016

Tulsa Public Schools: Preparing Kids for the Third Grade Turning Point

July 19th, 2016|

Third grade is a turning point in learning, where students transition from learning to read to reading to learn. Thus, many education systems now focus on early literacy. There’s a [...]

Jul 12,2016

2016 Police Projects: Back to the Whiteboards

July 12th, 2016|

A crucial but often overlooked consideration when working with data is: what is the best way to organise it? The way we organise our data can change not only how [...]

Jun 7,2016

DSSG 2016 Week One: Convergence and Priorities

June 7th, 2016|

Data Science for Social Good is now four years old. If we were a toddler, we’d be learning our alphabet and arithmetic. If we were a high school student, we’d [...]

Apr 28,2016

Introducing the Data Maturity Framework

April 28th, 2016|

In our four years of running the Data Science for Social Good Fellowship and the Center for Data Science and Public Policy, we have talked to hundreds of organizations about [...]

Apr 27,2016

You say you want Transparency and Interpretability?

April 27th, 2016|

We keep hearing and saying that in order to implement and correctly use machine learning and predictive models , they must be transparent and interpretable. That makes sense. You don't [...]

Feb 22,2016

Data Science For Social Good 2016 Applicants

February 22nd, 2016|

Fellow applications for the 2016 Summer Fellowship are all in and we have been busy reviewing the 900 we received! As we go through the very high (virtual) stack of applications, resumes, [...]

Jan 5,2016

Announcing Diogenes: all the Machine Learning code you’ll never have to write

January 5th, 2016|

At the Center for Data Science and Public Policy, we work on problems across different policy areas and develop machine learning (ML) solutions that span all these area , from education [...]

Dec 31,2015

The Greatest Technical Challenge of Our Day… Reading CSVs

December 31st, 2015|

Many data science projects follow the following workflow Define problem Get data Analyze the data (that may include building predictive models) Report the results of the analysis. Implement results into an [...]

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