Tutorial: NVIDIA Deep Learning Fundamentals

Date/Time: Sunday, August 5th 2018, 9:00am – 12:00pm
Presented by: Raymond Ptucha, Ph.D.
Assistant Professor of Computer Engineering, Rochester Institute of Technology, USA
NVIDIA Deep Learning Institute Certified Instructor and University Ambassador
Contact: rwpeec@rit.edu

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Bio sketch: Raymond Ptucha is an Assistant Professor in Computer Engineering and Director of the Machine Intelligence Laboratory at Rochester Institute of Technology. His research specializes in machine learning, computer vision, and robotics. Ray was a research scientist with Eastman Kodak Company where he worked on computational imaging algorithms and was awarded 31 U.S. patents with another 19 applications on file. He graduated from SUNY/Buffalo with a B.S. in Computer Science and a B.S. in Electrical Engineering. He earned a M.S. in Image Science from RIT. He earned a Ph.D. in Computer Science from RIT in 2013. Ray was awarded an NSF Graduate Research Fellowship in 2010 and his Ph.D. research earned the 2014 Best RIT Doctoral Dissertation Award. Ray is a passionate supporter of STEM education and is an active member of his local IEEE chapter and FIRST robotics organizations.

Target audience: Beginner. Participants should have a technical background and will benefit if they have some machine learning exposure.

Course description: This tutorial is an NVIDIA Deep Learning Institute (DLI) course. It offers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning and accelerated computing. In this half-day Deep Learning Fundamentals tutorial, participants will:

• Understand general terms and background of deep learning
• Leverage Deep Neural Networks (DNN) within the deep learning workflow to solve a real-world image classification problem using DIGITS
• Using provided cloud services, participants will use their own laptops to train, test, iteratively improve and deploy DNNs via a hands-on lab session

Agenda

• Deep Learning Demystified and Applied Deep Learning (lecture)
• Image Classification with DIGITS lab (hands-on session using provided cloud services)
• Neural network deployment lab (hands-on session using provided cloud services)