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Introduction of the Webinar
Artificial Intelligence (AI) is
solving problems that seemed well beyond our reach just a few years back.
Using deep learning, the fastest growing segment of AI,
computers are now able to learn and recognize patterns from data that
were considered too complex for expert written software.
Today, deep learning is transforming every industry, including
automotive, healthcare, retail and financial services. This introduction
to deep learning will explore key fundamentals and
opportunities, as well as current challenges and how to address
them. Highlights include:Demystifying Artificial Intelligence,
Machine Learning and Deep LearningKey challenges
organizations face in adopting this new approachHow
GPU deep learning and software, along with training resources,
can deliver breakthrough results.
Biography of Speaker :
Dr Charles CHEUNG is
currently a Deep Learning Solution Architect and Data Scientist
in NVIDIA AI Technology Center Hong Kong. Prior joining NVIDIA, he
worked in Hong Kong Applied Science Technology and Research Institute for
applied research. He leads the project team of machine vision group to develop deep learning solution
for industrial defect inspection. The solution greatly helps the factory to
increase the production stability and reduce the inspection time for quality
control department.
Charles obtained the bachelor’s degree and PhD degree in applied and computational
mathematics from Hong Kong Baptist University. His research focus on
computational science, partial differential equations, computer vision and
artificial intelligence.
Registration & Enquiries
This webinar is free of charge with maximum capacity of 350.
Applications will be accepted on a first-come first-served basis. For
registration, please complete the online registration by clicking the direct
enrolment link https://bit.ly/36jpdgV {Thanks for the support, the enrollment has ended}. Electronic CPD
certificate will be issued to those who attend the 23 Nov webinar and complete
the event survey. The deadline for registration is by 17 Nov 2020.