How to Beat the Traffic (at Strata)

This week I had the opportunity to attend and speak at one of the biggest Big Data conferences of the year.

The Strata conferences run by O’Reilly have been running for the last few years and in many ways have driven the awareness and adoption of data science and predictive analytics.

My colleagues Alexander Kagoshima and Noelle Sio, and I talked about recent work we’ve been doing on how to use machine learning techniques to understand traffic flows in major cities and predict when travel disruptions will end. The talk seemed to be well received and generated a lot of questions and comments both at the conference and on Twitter. This recent post on the Pivotal blog explains more about the projects and the overall goals.

As part of the disruption prediction work I built a simple web app which displays the predictions for currently active incidents.

Video of the talk will be available through O’Reilly, and our slides are available on Slideshare:

If you are interested in this or other projects the Pivotal Data Labs team have worked on, there is a lot more information on the official Pivotal site.

 

Ian

A physicist by training, I am curious about the world around us, from the smallest to the largest scales. I am now a part of the Pivotal Data Science team and work on interesting data science and predictive analytics projects across a wide range of industries. On Twitter I'm @ianhuston, and on Github I'm ihuston.

 

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