97th AMS Annual Meeting | 22–26 January 2017 | Seattle, WA

Cloud-based Data Exploration and Machine Learning on environmental datasets

22 January 2017, Seattle, WA Location: Conf Cntr: Skagit 3
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Preliminary Agenda CloudData

The growing availability of cloud-based computational power has made possible new data exploration and machine learning techniques. This course will present steps of a data exploration and implementation of machine learning techniques using recently developed cloud based tools. The course will discuss the type of problems best tackled with these new techniques; differences with typically PC based AI and data exploration methods. The course will continue with a demonstration focused on an environmental data set. Attendees will then be provided access to a cloud based data set and machine learning tools to become more familiar and experiment with the techniques themselves. The data set will be a combination of nationwide weather predictions with an operational data set. The short course will close with a discussion of the best use of AI cloud based methods.


All attendees will need to bring a laptop (with power adapter) that has the ability to connect wirelessly to the internet using the conference center network. Additional Instructions will be emailed to registered attendees before the course begins. 

For more information please contact the short course organizers:

Course Instructor:         Valliappa Lakshmanan;  lakshmanok@gmail.com
Course Admin:                Philippe Tissot; philippe.tissot@tamucc.edu
                                      Amy McGovern; amy@bachman.cs.ou.edu


Short Course Registration

All short course/workshop attendees must register and wear a badge/ribbon. Short course/workshop registration is not included in the 97th Annual Meeting registration, and short course/workshop registration does not include registration for the 97th AMS Annual Meeting.

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