News

17 April, 2018

NVIDIA-BDI Deep Learning Hands-On Labs

HKUST Big Data Institute (BDI) is excited to partner with NVIDIA Deep Learning Institute again to organize a half-day practical Deep Learning Fundamentals workshop on 17 April 2018.

The NVIDIA Deep Learning Institute delivers hands-on training for developers, data scientists, and engineers. The program is designed to help them to get started with training, optimizing, and deploying neural networks to solve real-world problems across diverse industries such as self-driving cars, healthcare, online services, and robotics.



In the workshop, Mr Li Chen, a postgraduate student of Prof Kai Chen, Associate Professor of Department of Computer Science and Engineering (CSE) of HKUST, introduced the Deep Learning Research. Mr Li Chen is the final year PhD student in CSE, Microsoft Research Asia PhD Fellow, working on data centers, networking, parallel computing, and AI frameworks.

AI is a broad field of study about using computers to perform tasks that require human-level intelligence. It has been around since the 50’s, playing games like tic-tac-toe and checkers, and inspiring scary sci-fi movies. But it was limited to practical applications.

It was known that Machine Learning is an approach to AI that uses statistics techniques to construct a model from observed data. It generally relies on human-defined classifiers or “feature extractors” that can be as simple as a linear regression or slightly more complicated “Bag of Words” analysis that made email SPAM filters possible.

Deep Learning is a Machine Learning technique that automates the creation of feature extractors, using large amounts of data to train complex “deep neural networks”.



Today’s workshop is the 3rd cooperation between HKUST and NVIDIA, and it attracted over 100 HKUST’s students and staff.

This is the third time BDI collaborated with NVIDIA to organize the workshop together. Over 100 HKUST students and staff were attracted to attend. BDI will organize this kind of workshop in the coming months.