Making AI Work: Machine and Deep Learning

Penn State IT

Artificial intelligence (AI) is often claimed to have the promise of transforming and possibly taking over our society. But there seems to be little understanding of how it really works or its current limitations.
Join us online (Zoom) or in person to learn more about the most popular and useful AI methodology, machine learning. Dr. Lee Giles, the David Reese Professor at the College of Information Sciences and Technology at Penn State, will discuss what a machine learning problem is and what it can do, as well as introduce a new machine learning model, deep learning. 
In an effort to provide context to artificial intelligence's power and limitations, the talk will highlight the basics of implementing AI into actual problems. It will also dive into the different classes and memory models of deep learning.
View the live stream of this CyberScience Seminar here: <A HREF="https://psu.zoom.us/j/633640886" DATA-MSYS-CLICKTRACK="0" REL="nofollow noopener noreferrer">https://psu.zoom.us/j/633640886</A>.  
Seating is limited. 
 
<P CLASS="Paragraph SCXW199793120" STYLE="margin: 0px; padding: 10px 0px 0px; color: #6f7287; font-family: 'Neue Plak', -apple-system, system-ui, Roboto, 'Helvetica Neue', Helvetica, Tahoma, Arial, sans-serif; font-size: 15px; letter-spacing: 0.5px;">This event is part of the ICS CyberScience Seminars, a monthly lecture series exploring cutting-edge topics related to computational and big data research.
 
 
<H2 CLASS="Paragraph SCXW199793120">About the Speaker</H2>
<IMG ALT="" SRC="https://cdn.evbuc.com/eventlogos/268351370/leegiles.jpg">
 Dr. C. Lee Giles is the David Reese Professor at the College of Information Sciences and Technology at the Penn State. His current research interests are in intelligent information processing systems. He is also graduate professor of computer science and engineering, courtesy professor of supply chain and information systems, and director of the intelligent systems research laboratory.  He recently became a teaching and learning technology fellow and the interim associate dean of research for IST. He directs the Next Generation CiteSeer, CiteSeerx project and codirects the ChemXSeer project at Penn State. He has been associated with Columbia University, the University of Maryland, University of Pennsylvania, Princeton University, and the University of Trento.

Making AI Work: Machine and Deep Learning

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Making AI Work: Machine and Deep Learning

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