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2015 Prepared Talk Proposals

191 bytes added, 15:31, 22 October 2014
Added Data Science proposal by Devon Smith
* Geoffrey Boushey, geoffrey.boushey@ucsf.edu, UCSF Library
Academic libraries are increasingly responsible for providing ingest, search, discovery, and analysis for data sets. Emerging techniques from data science and machine learning can provide librarians and developers with an opportunity to generate new insights and services from these document collections. This presentation will provide a brief overview of common machine learning classification techniques, then dive into a more detailed example using a random forest to assign keywords to research data sets. The talk will emphasize the insight that can be gained from machine learning rather than the inner workings of the algorithms. The overall goal of this presentation is to provide librarians and developers with the context to recognize an opportunity to apply machine learning categorization techniques at their home campuses and organizations.
 
== Data Science in Libraries ==
* Devon Smith, smithde@oclc.org, OCLC
 
Data Science is increasing in buzz and hype. I'll go over what it is, what it isn't, and how it fits in libraries.
 
 
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