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June 2018

Duke Machine Learning Summer School

June 25 - June 29
Duke Fuqua School of Business

Machine learning methodology is primarily concerned with designing appropriate models/algorithms for datasets and problems, plus the capacity to learn the model parameters given data (made more complex with "big data"). Machine-learning has a broad range of applications, from making improved diagnoses in health care to tailoring products and ads to individual customers. There are many applications of machine learning in health, science, business, engineering, social science, and the humanities. With increasing access to massive datasets, and to significant advances in…

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July 2018

Staff TechFair

July 11 @ 11:00 am - 2:00 pm
Technology Engagement Center (TEC), Telcom Building, Telcom Building
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NSF Cyber Carpentry Workshop: Data Lifecycle Training (RENCI, UNC-CH)

July 16 - July 27
RENCI (Chapel Hill)

For today‚Äôs graduate and post-doctoral students, conducting research often starts by trying to make sense of the many tools, technologies, and work environments used in data-intensive research and computing. Fortunately, there is help in navigating this new research landscape. The NSF Cyber Carpentry Workshop: Data Lifecycle Training is a two-week summer workshop aimed at helping graduate students understand the many aspects of the data-intensive computing environment. Even more important, the workshop will focus on bridging the gap between domain scientists…

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August 2018

Data+ 2018 Poster Session

August 3 @ 2:00 pm - 3:30 pm
Energy Hub Lobby, Gross Hall 100
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Building a machine learning health system (Nigam H. Shah, Stanford)

August 15 @ 11:00 am - 12:00 pm
Hock Building, 2nd Floor, CRTP Classroom

Abstract: Using Electronic Health Records (EHRs), it is possible to examine the outcomes of decisions made by doctors during routine care and generate evidence from the collective experience of patients. We will discuss our efforts at Stanford Medicine for transforming unstructured EHR data to discover hidden trends, build predictive models, and drive comparative effectiveness studies in a learning health system. Dr. Nigam H. Shah is an Associate Professor of Medicine at the Stanford University. Dr. Shah's research focuses on combining machine…

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April 2019

Bass Connections Showcase 2019

April 17, 2019 @ 3:30 pm - 6:00 pm
Penn Pavilion (West Campus)
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