Practical Optimization for Stats Nerds

For our March Data Science DC Meetup, we are excited to have Ryan J. O’Neil join us to talk about statistical models for machine learning -- where techniques from optimization and decision modelling will be discussed. Ryan manages the Decision Engineering team of Grubhub, along with his research into dynamic fleet management for his PhD.

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Agenda:

• 6:30pm -- Networking, Empanadas, and Refreshments

• 7:00pm -- Introduction, Announcements

• 7:15pm -- Presentation and Discussion

• 8:30pm -- Data Drinks (Tonic , 2036 G St NW)

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Abstract:

Many models important to inferential statistics and machine learning use some form of optimization under the hood. For example, least squares regression and support vector machines are both implemented as simple optimization models. With the right tools in your hands, optimization can do so much more! This talk shows how to implement familiar statistical models directly using optimization solvers, how to extend those models in interesting ways, and then how to do more general decision modeling using the same technologies.

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Bio: Ryan J. O’Neil

http://photos1.meetupstatic.com/photos/event/d/e/1/5/600_459116853.jpeg

Ryan J. O’Neil has worked in software (The Washington Post, Blackboard) and logistics (Grubhub, Zoomer Delivery, MITRE) for over 15 years. As Grubhub's Director of Decision Engineering, he manages by day (and night) their Decision Engineering team, developing capabilities for business modeling and optimization. Some of his recent work involves dynamic vehicle routing algorithms and large-scale simulation of routing logistics. By later night, Ryan writes his dissertation on dynamic fleet management for the PhD program in Systems Engineering & Operations Research at George Mason University, and tends the home bar for his wife and their cat.

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Sponsors:

This event is sponsored by the George Washington Business School MS in Business Analytics Program (http://business.gwu.edu/programs/specialized-masters/m-s-in-business-analytics/academic-program/), Statistics.com (http://bit.ly/12YljkP), Elder Research (http://datamininglab.com/), Novetta (https://www.novetta.com/), Booz Allen Hamilton (https://www.boozallen.com/consulting/strategic-innovation/nextgen-analytics-data-science), and AOL (http://engineering.aol.com/). (Would your organization like to sponsor too? Please get in touch! (http://www.datacommunitydc.org/sponsorship/data-science-dc-sponsorship))